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一类Markov跳变神经网络的时滞相关鲁棒稳定性 被引量：2

Delay-dependent robust stability for a class of Markov jumping neural networks
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摘要 针对一类Markov跳变神经网络,研究了其在系统参数不确定情况下的全局鲁棒稳定性。利用Leibniz-Newton公式对原系统进行等价变换,基于Lyapunov稳定性理论,并结合Moon不等式得到了此类Markov跳变神经网络时滞相关均方鲁棒稳定性的判别条件。所得结果以线性矩阵不等式(linear matrix inequality,LMI)的形式给出,容易被Matlab中的LMI工具箱验证。最后,通过一个算例验证了所得结论的有效性。 The robust stability for a class of neural networks with Markov jumping parameters is investiga- ted. An equivalent transformation is made for the original system by the Leibniz-Newton formula. By applying Lyapunov stability theory and associating with Moon＇s inequality, the delay dependent robust stability condition for the Markov jumping neural networks is established. The results are given in the form of linear matrix inequality （LMI） and can be solved readily by the LMI tool box of Matlab. Finally, a numerical example is provided to illustrate the effectiveness of the theoretical results.
作者 盛立 杨慧中
机构地区 江南大学通信与控制工程学院
出处 《系统工程与电子技术》 EI CSCD 北大核心 2009年第11期2698-2702,共5页 Systems Engineering and Electronics
基金 国家自然科学基金(60674092)资助课题
关键词 神经网络 时滞相关鲁棒稳定性 LYAPUNOV泛函 MARKOV跳变 线性矩阵不等式 neural network delay-dependent robust stability Lyapunov functional Markov jumping linear matrix inequality
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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参考文献13

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同被引文献27

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引证文献2

系统工程与电子技术
2009年 第11期

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