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Stochastic stability analysis of neutral-type impulsive neural networks with mixed time-varying delays and Markovian jumping

机译:混合时变时滞和马尔可夫跳跃的中立型脉冲神经网络的随机稳定性分析

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摘要

In this paper, the stochastic stability problem of neutral-type impulsive neural networks (NINNs) with mixed time-varying delays and Markovian jumping is investigated. By utilizing the Lyapunov-Krasovkii functional approach and linear matrix inequality (LM1) technique, we obtain some novel globally exponentially stable results. Delay-dependent sufficient condition for the above problem is obtained, which is usually less conservative than delay-independent ones. An example is given to show the effectiveness of the obtained results.
机译:研究具有混合时变时滞和马尔可夫跳跃的中立型脉冲神经网络(NINN)的随机稳定性问题。通过使用Lyapunov-Krasovkii函数方法和线性矩阵不等式(LM1)技术,我们获得了一些新颖的全局指数稳定结果。对于上述问题,获得了时延相关的充分条件,通常比时延无关的条件保守。给出一个例子来说明所获得结果的有效性。

著录项

  • 来源
    《Neurocomputing》 |2010年第15期|P.2689-2695|共7页
  • 作者单位

    School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, People's Republic of China;

    rnSchool of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, People's Republic of China;

    rnSchool of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, People's Republic of China;

    rnSchool of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, People's Republic of China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    neutral-type neural networks (NNNs); delay-dependent criteria; stochastic stability; impulsive; markovian jumping; time-varying delay;

    机译:中性型神经网络(NNN);延迟相关标准;随机稳定性浮躁;马氏跳时变延迟;

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