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具有无穷时滞高阶模糊Cohen-Grossberg神经网络的稳定性

郑伟范 张继业

郑伟范, 张继业. 具有无穷时滞高阶模糊Cohen-Grossberg神经网络的稳定性[J]. 西南交通大学学报, 2014, 27(6): 1052-1060. doi: 10.3969/j.issn.0258-2724.2014.06.017
引用本文: 郑伟范, 张继业. 具有无穷时滞高阶模糊Cohen-Grossberg神经网络的稳定性[J]. 西南交通大学学报, 2014, 27(6): 1052-1060. doi: 10.3969/j.issn.0258-2724.2014.06.017
ZHENG Weifan, ZHANG Jiye. Stability of High Order Fuzzy Cohen-Grossberg Neural Networks with Unbounded Time Delays[J]. Journal of Southwest Jiaotong University, 2014, 27(6): 1052-1060. doi: 10.3969/j.issn.0258-2724.2014.06.017
Citation: ZHENG Weifan, ZHANG Jiye. Stability of High Order Fuzzy Cohen-Grossberg Neural Networks with Unbounded Time Delays[J]. Journal of Southwest Jiaotong University, 2014, 27(6): 1052-1060. doi: 10.3969/j.issn.0258-2724.2014.06.017

具有无穷时滞高阶模糊Cohen-Grossberg神经网络的稳定性

doi: 10.3969/j.issn.0258-2724.2014.06.017
基金项目: 

国家自然科学基金资助项目(11172247,61273021,61100118,61373009)

中央高校基本科研业务费专项资金资助项目(SWJTU11BR091)

四川省科技支撑计划资助项目(2013GZX0166)

Stability of High Order Fuzzy Cohen-Grossberg Neural Networks with Unbounded Time Delays

  • 摘要: 利用M矩阵理论和矩阵不等式、矢量Lyapunov 函数法,研究了一类具有无穷时滞的高阶模糊Cohen-Grossberg神经网络的全局指数稳定性.在不要求神经网络激活函数的单调递增性、可微性及Lipschitz连续等假设条件下,得到了该类神经网络平衡点的存在性和唯一性,以及全局指数稳定性的代数判据.该判据为M矩阵的显式形式,与系统的时间滞后以及反应扩散无关,易于在应用中进行检验.最后,通过仿真算例,验证了该方法的正确性和有效性.

     

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出版历程
  • 收稿日期:  2013-08-16
  • 刊出日期:  2014-12-25

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