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New stability analysis for neutral type neural networks with discrete and distributed delays using a multiple integral approach

机译:带有多重积分方法的具有离散和分布时滞的中立型神经网络的新稳定性分析

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摘要

This study is concerned with the problem of stability analysis for neutral type neural networks with discrete and distributed delays. By making full use of a novel integral inequality proved to be less conservative than the celebrated Jensen's inequality, new stability results are established. Besides, a multiple integral inequality is also proposed firstly in neutral type neural networks with mixed delays. Based on the integral inequality, improved stability criteria in terms of linear matrix inequalities (LMIs) are derived by constructing an appropriate Lyapunov-Krasovskii functional including the multiple integral terms showed to have a great potential efficient in practice. Furthermore, less conservative stability results are obtained by dividing the distributed delay into multiple nonuniformly subinterval. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results.
机译:这项研究涉及具有离散和分布时滞的中立型神经网络的稳定性分析问题。通过充分利用新颖的积分不等式,证明其不如著名的詹森不等式那么保守,从而建立了新的稳定性结果。此外,还首先在具有混合时滞的中立型神经网络中提出了多个积分不等式。基于积分不等式,通过构建一个适当的Lyapunov-Krasovskii泛函(包括多个在实践中显示出很大潜力的有效积分),可以得出有关线性矩阵不等式(LMI)的改进的稳定性标准。此外,通过将分布式延迟划分为多个不均匀的子间隔,可获得较少的保守稳定性结果。最后,通过数值例子说明了理论结果的有效性和优势。

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  • 来源
    《Journal of the Franklin Institute》 |2015年第1期|155-176|共22页
  • 作者单位

    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;

    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;

    School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China,Key Laboratory for Neuroinformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu 611731, China;

    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;

    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;

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