|
| 一类中立型比例时滞神经网络的全局指数稳定性 |
| Global Exponential Stability of a Class of Neutral Neural Network with Proportional Delay |
| 投稿时间：2025-02-15 修订日期：2025-03-31 |
| DOI： |
| 中文关键词: 中立型微分方程 比例时滞 全局指数稳定 最大值范数 Gronwall积分不等式 |
| 英文关键词:neutral differential equation, proportional time delay, global exponential stability, Maximum norm, Gronwall integral inequality |
| 基金项目:湖南省教育厅科学研究一般项目，24C0894 |
|
| 摘要点击次数: 0 |
| 全文下载次数: 0 |
| 中文摘要: |
| 信息传输过程中时滞现象难以避免,而时滞往往会对神经网络的性态产生结构性的影响,因而时滞神经网络的全局稳定性是系统控制的一个重要目标。通过构造向量函数的正无穷范数(最大值范数)和矩阵的1-范数、结合Gronwall积分不等式,得到了一类具比例时滞的中立型神经网络全局指数稳定的充分性条件,所得结果与时滞有关。此外,通过举例对结果进行了数值模拟。 |
| 英文摘要: |
| It is difficult to avoid the delays in the process of information transmission, and the delays often have a structural impact on the property of a neural network. Hence, it is an important target to study the global stability of the system for the control of a delayed neural network. By constructing the Positive Infinite Norm (Maximum Norm) for a vector function and the One-norm for a matrix, we obtained the sufficient condition of the global exponential stability for a neutral neural network with proportional time delay, and the results are related to the time delay. Furthermore, the results were illustrated by examples. |
| 查看/发表评论 下载PDF阅读器 |
| 关闭 |