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带有时滞的Clifford值神经网络的全局指数稳定性

舒含奇 宋乾坤

舒含奇, 宋乾坤. 带有时滞的Clifford值神经网络的全局指数稳定性[J]. 应用数学和力学, 2017, 38(5): 513-525. doi: 10.21656/1000-0887.370319
引用本文: 舒含奇, 宋乾坤. 带有时滞的Clifford值神经网络的全局指数稳定性[J]. 应用数学和力学, 2017, 38(5): 513-525. doi: 10.21656/1000-0887.370319
SHU Han-qi, SONG Qian-kun. Global Stability of Clifford-Valued Recurrent Neural Networks With Mixed Time-Varying Delays[J]. Applied Mathematics and Mechanics, 2017, 38(5): 513-525. doi: 10.21656/1000-0887.370319
Citation: SHU Han-qi, SONG Qian-kun. Global Stability of Clifford-Valued Recurrent Neural Networks With Mixed Time-Varying Delays[J]. Applied Mathematics and Mechanics, 2017, 38(5): 513-525. doi: 10.21656/1000-0887.370319

带有时滞的Clifford值神经网络的全局指数稳定性

doi: 10.21656/1000-0887.370319
基金项目: 国家自然科学基金(61273021;61473332)
详细信息
    作者简介:

    舒含奇(1994—), 女, 硕士生(E-mail: shuhanqi@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 Stability of Clifford-Valued Recurrent Neural Networks With Mixed Time-Varying Delays

Funds: The National Natural Science Foundation of China(61273021; 61473332)
  • 摘要: 研究了带有离散时滞和分布时滞的Clifford值递归神经网络的全局指数稳定性问题.首先运用M矩阵的性质和不等式技巧证明了Clifford值递归神经网络平衡点的存在性和唯一性;然后通过数学分析方法,得到了Clifford值递归神经网络全局指数稳定的判定条件;最后数值仿真例子验证了获得结果的有效性.
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  • 被引次数: 0
出版历程
  • 收稿日期:  2016-10-17
  • 修回日期:  2017-03-23
  • 刊出日期:  2017-05-15

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