Stability analysis for neutral-type generalized neural networks with delays

被引：0
|
作者：
Zhu, Jin [1 ]
Li, Tai-Fang [2 ]
机构：
[1] Bohai Univ, Coll Math & Sci, Jinzhou 121000, Peoples R China
[2] Bohai Univ, Coll Control Sci & Engn, Jinzhou 121000, Peoples R China
来源：
2022 41ST CHINESE CONTROL CONFERENCE (CCC) | 2022年
关键词：
Neutral-Type Generalized Neural Networks; Asymptotically Stable; Lyapunov Functional; CRITERIA;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper deals with the issue of asymptotical stability for neutral-type generalized neutral neural networks. A new augmented vector with the derivative of state is introduced in Lyapunov-Krasovskii functional. The stability criteria are obtained by constructing the suitable Lyapunov-Krasovskii functional and utilizing the free-matrix-based integral inequality. The zero equation is added to the derivative of Lyapunov-Krasovskii functional, which decreases conservatism. The effectiveness and feasibility of the proposed methods are demonstrated by numerical example.
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页码：1177 / 1182
页数：6
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