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具有泄漏时滞的复值神经网络的全局同步性

闫欢 赵振江 宋乾坤

闫欢, 赵振江, 宋乾坤. 具有泄漏时滞的复值神经网络的全局同步性[J]. 应用数学和力学, 2016, 37(8): 832-841. doi: 10.21656/1000-0887.370168
引用本文: 闫欢, 赵振江, 宋乾坤. 具有泄漏时滞的复值神经网络的全局同步性[J]. 应用数学和力学, 2016, 37(8): 832-841. doi: 10.21656/1000-0887.370168
YAN Huan, ZHAO Zhen-jiang, SONG Qian-kun. Global Synchronization of Complex-Valued Neural Networks With Leakage Time Delays[J]. Applied Mathematics and Mechanics, 2016, 37(8): 832-841. doi: 10.21656/1000-0887.370168
Citation: YAN Huan, ZHAO Zhen-jiang, SONG Qian-kun. Global Synchronization of Complex-Valued Neural Networks With Leakage Time Delays[J]. Applied Mathematics and Mechanics, 2016, 37(8): 832-841. doi: 10.21656/1000-0887.370168

具有泄漏时滞的复值神经网络的全局同步性

doi: 10.21656/1000-0887.370168
基金项目: 国家自然科学基金(61273021; 61473332)
详细信息
    作者简介:

    闫欢(1991—),女,硕士生(E-mail: huanyancquc@163.com);赵振江(1961—),男,教授,硕士(E-mail: zhaozjcn@163.com);宋乾坤(1963—),男,教授,博士(通讯作者. E-mail: qiankunsong@163.com).

  • 中图分类号: O175.13

Global Synchronization of Complex-Valued Neural Networks With Leakage Time Delays

Funds: The National Natural Science Foundation of China(61273021; 61473332)
  • 摘要: 研究了一类具有泄漏时滞的复值神经网络的全局同步性问题.在不要求激励函数可分离为实部函数和虚部函数的条件下,通过构造合适的Lyapunov-Krasovskii泛函,并运用驱动响应同步方法、自由权矩阵方法和矩阵不等式技巧,获得了具有泄漏时滞的复值神经网络全局同步性的充分条件和同步控制器设计方法.给出的判据是由复值线性矩阵不等式表示的,易于MATLAB软件的YALMIP Toolbox实现.数值仿真实例验证了获得结果的有效性.
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出版历程
  • 收稿日期:  2016-05-27
  • 刊出日期:  2016-08-15

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