Novel global polynomial stability criteria of impulsive complex-valued neural networks with multi-proportional delays

被引：0
|
作者：
Yongkang Zhang
Liqun Zhou
机构：
[1] Tianjin Normal University,School of Mathematical Sciences
来源：
Neural Computing and Applications | 2022年 / 34卷
关键词：
Complex-valued neural networks; Impulsive effects; Proportional delays; Global polynomial stability;
D O I：
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学科分类号：
摘要：
The impulsive complex-valued neural networks (CVNNs) with multi-proportional delays (MPDs) are considered. By setting up a suitable Lyapunov–Krasovskii functional (L-KF) and utilizing the matrix inequality skills, several delay-dependent criteria for examining the global polynomial stability (GPS) of the CVNNs are built via linear matrix inequalities (LMIs), which can be verified numerically using the valid YALMIP toolbox in MATLAB. An example with simulations is presented to highlight the potency and the efficiency of the raised criteria.
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页码：2913 / 2924
页数：11
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