Finite-Time Stabilization for Static Neural Networks with Leakage Delay and Time-Varying Delay

被引：0
|
作者：
Xiaoyu Zhang
Yuan Yuan
Xiaodi Li
机构：
[1] Shandong Normal University,School of Mathematics and Statistics
[2] Southwest University,Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering
[3] Memorial University of Newfoundland,Department of Mathematics and Statistics
来源：
Neural Processing Letters | 2020年 / 51卷
关键词：
Finite-time stability; Static neural networks; Time-varying delay; Leakage delay; Linear matrix inequality (LMI);
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The problem of finite-time stabilization (FTS) for static neural networks (SNNs) with leakage delay and time-varying delay is investigated in this paper. By introducing an auxiliary function and utilizing the Lyapunov stability theory, we derive some sufficient criteria for FTS in terms of linear matrix inequalities (LMIs). Two feedback controllers are designed based on two different Lyapunov functions, which can be easily solved via MATLAB LMI toolbox, to guarantee the FTS for the SNNs. Finally, two numerical examples are given to illustrate the efficiency of our results.
引用
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页码：67 / 81
页数：14
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