Finite-time synchronization control of fractional-order memristive neural networks with time varying delays

被引:0
|
作者
Liu, Yihong [1 ]
Sun, Yeguo [2 ]
机构
[1] Huainan Normal Univ, Sch Comp Sci, Huainan 232038, Peoples R China
[2] Huainan Normal Univ, Sch Finance & Math, Huainan 232038, Peoples R China
来源
PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020) | 2020年
基金
中国国家自然科学基金;
关键词
finite-time synchronization; fractional-order memristive neural networks; time varying delays; STABILITY;
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
This paper considers the finite-time synchronization control of fractional-order memristive neural networks with time varying delays. By utilizing the properties of fractional calculus and fractional-order comparison principle, we propose a new lemma. Base on the new lemma and some analysis techniques, some novel criteria are given to ensure finite-time synchronization of fractional-order memristive neural networks with time varying delays by adopting a delay-dependent feedback controller, and the upper bound of the setting time for synchronization is estimated. Finally, numerical simulations are given to verify the effectiveness of the obtained results and the superiority of the new finite-time stability theorem.
引用
收藏
页码:3231 / 3237
页数:7
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