Anti-synchronization Analysis of Fractional-Order Neural Networks with Time-Varying Delays

被引：0
|
作者：
Xu, Minglin [1 ]
Liu, Peng [1 ]
Kong, Minxue [1 ]
Sun, Junwei [1 ]
机构：
[1] Zhengzhou Univ Light Idustry, Coll Elect & Informat Engn, Zhengzhou, Peoples R China
来源：
2020 12TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI) | 2020年
关键词：
fractional-order; neural network; time-varying delays; anti-synchronization; MEMRISTOR; STABILITY; DYNAMICS; SYSTEMS;
D O I：
10.1109/icaci49185.2020.9177766
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper deals with the anti-synchronization problem of fractional-order neural networks with time-varying delays. By using the properties of fractional calculus, sufficient criteria are deduced for realizing the anti-synchronization of fractional-order neural networks with time-varying delays. In addition, sufficient criteria for anti-synchronization in Mittag-Leffler sense are derived for fractional-order neural networks without time delay. The results in this paper are also applicable for anti-synchronization results of integer-order neural networks. Three numerical examples are proposed to verify the validity of the theoretical results.
引用
收藏
页码：585 / 590
页数：6
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