首页> 外文期刊>Neurocomputing >Finite-time synchronization of memristive neural networks with discontinuous activation functions and mixed time-varying delays
【24h】

Finite-time synchronization of memristive neural networks with discontinuous activation functions and mixed time-varying delays

机译:具有不连续激活函数和混合时变延迟的忆阻神经网络的有限时间同步

获取原文
获取原文并翻译 | 示例
           

摘要

This paper is concerned with the issue of the finite-time adaptive synchronization and finite-time synchronization of memristive neural networks with discontinuous activation functions and mixed timevarying delays. For synchronizing the drive-response memristive neural networks in finite time, an adaptive state-feedback controller and a state-feedback controller are proposed, respectively. Then by using the theories of differential inclusions and set-valued map, the synchronization issue of drive-response memristive neural networks with discontinuous activation functions and mixed time-varying delays is transformed into the stabilization issue of the error system. Moreover, based on the stability theory, Forti Lemma and Hardy inequality, some novel algebraic synchronization criteria are deduced to ensure the finite-time adaptive synchronization and finite-time synchronization of memristive neural networks with discontinuous activation functions and mixed time-varying delays under the adaptive state-feedback controller and the state-feedback controller. And the settling times for finite-time adaptive synchronization and finite-time synchronization are given. Furthermore, it is hard to estimate the initial conditions for a large system, so the settling times in this paper are not dependent on initial conditions of system. Finally, an example is provided to demonstrate the effectiveness of the obtained results. (C) 2019 Elsevier B.V. All rights reserved.
机译:本文涉及具有不连续激活函数和混合时变时滞的忆阻神经网络的有限时间自适应同步和有限时间同步问题。为了在有限的时间内同步驱动响应忆阻神经网络,分别提出了一种自适应状态反馈控制器和状态反馈控制器。然后,利用微分包含和集值映射理论,将具有不连续激活函数和时变时滞的驱动响应忆阻神经网络的同步问题转化为误差系统的稳定问题。此外,基于稳定性理论,Forti Lemma和Hardy不等式,推导了一些新颖的代数同步准则,以确保在不连续激活函数和混合时变时滞下的忆阻神经网络的有限时间自适应同步和有限时间同步。自适应状态反馈控制器和状态反馈控制器。给出了有限时间自适应同步和有限时间同步的建立时间。此外,很难估计大型系统的初始条件,因此本文中的建立时间不取决于系统的初始条件。最后,提供一个例子来证明所获得结果的有效性。 (C)2019 Elsevier B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号