| 具有不确定性的分数阶时滞复值神经网络无源性 |
| |
| 引用本文： | 陈宇,周博,宋乾坤.具有不确定性的分数阶时滞复值神经网络无源性[J].应用数学和力学,2021,42(5):492-499. |
| |
| 作者姓名： | 陈宇 周博 宋乾坤 |
| |
| 作者单位： | 重庆交通大学 数学与统计学院, 重庆 400074 |
| |
| 基金项目： | 重庆市教委科学技术研究项目(KJZD M202000701)；国家自然科学基金(61773004) |
| |
| 摘 要： | 该文研究了一类具有不确定性和时滞的分数阶复值神经网络无源性问题，未将复值神经网络模型拆分成两个实值系统，而是将复值系统当成一个整体直接进行处理.通过构造恰当的Lyapunov函数，并利用矩阵不等式技巧，建立了网络无源性的线性矩阵不等式判据.给出的数值例子和仿真验证了获得结论的可行性和有效性.
|
| 关 键 词： | 复值神经网络 分数阶 无源性 时滞 不确定性 |
| 收稿时间： | 2020-10-15 |
Passivity of Fractional-Order Delayed Complex-Valued Neural Networks With Uncertainties |
| |
| Affiliation: | College of Mathematics and Statistics, Chongqing Jiaotong University,Chongqing 400074, P.R.China |
| |
| Abstract: | The passivity for a class of fractional-order delayed complex-valued neural networks with uncertainties was studied. The complex-valued neural network was not divided into 2 real-valued neural networks, but treated as a whole. Through construction of the appropriate Lyapunov function and application of the inequality technique, the sufficient criterion in the form of the linear matrix inequality was established to ensure the passivity of the considered neural networks. Numerical examples and simulations verify the feasibility and effectiveness of the obtained conclusion. |
| |
| Keywords: | |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《应用数学和力学》浏览原始摘要信息 |
|
点击此处可从《应用数学和力学》下载全文 |
