时滞切换不确定神经网络系统的指数稳定性
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国家自然科学基金资助项目(11572264),广东省普通高校创新人才资助项目(2016KQNCX103)和韩山师范学院青年科学基金(LQ201301)


Exponential stability of time⁃delayed switched uncertain neural networks systems
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    摘要:

    本文研究了具有无穷时滞切换不确定细胞神经网络(UCNNs)系统任意切换下的指数稳定性. 利用同胚映射和M?矩阵理论, 得到UCNNs 系统平衡点存在性, 唯一性和指数稳定性的充分条件; 利用Lyapunov泛函方法, 研究了时滞切换UCNNs 系统任意切换下的鲁棒指数稳定性, 并得到确保系统全局指数稳定的充分条件.

    Abstract:

    In this paper, a class of switched uncertain cellular neural networks (UCNNs) systems with unbounded delay under arbitrary switching were investigated. By using the homeomorphic mapping theorem and M?matrix theory, the sufficient conditions for the existence, uniqueness and exponential stability of the equilibrium point of UCNNs systems with unbounded delay were obtained. By Lyapunov functional approach, we studied the robust exponential stability of arbitrary switching delay UCNNs systems. Sufficient conditions to guarantee the global exponential stability of switched delay UCNNs systems were also derived, and the stability was robust to both parameter perturbations and switching perturbations.

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薛焕斌,张继业.时滞切换不确定神经网络系统的指数稳定性[J].动力学与控制学报,2018,16(1):65~71; Xue Huanbin, Zhang Jiye. Exponential stability of time⁃delayed switched uncertain neural networks systems[J]. Journal of Dynamics and Control,2018,16(1):65-71.

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  • 收稿日期:2016-12-19
  • 最后修改日期:2017-02-27
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  • 在线发布日期: 2018-02-09
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