Global Mittag-Leffler stabilization of fractional-order complex-valued memristive neural networks

被引：41
|
作者：
Chang, Wenting [1 ]
Zhu, Song [1 ]
Li, Jinyu [1 ]
Sun, Kaili [1 ]
机构：
[1] China Univ Min & Technol, Sch Math, Xuzhou 221116, Jiangsu, Peoples R China
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2018年 / 338卷
关键词：
Fractional-order; Complex-valued; Memristive neural networks; Global Mittag-Leffler stability; EXPONENTIAL STABILITY; SYNCHRONIZATION; EXISTENCE; DYNAMICS;
D O I：
10.1016/j.amc.2018.06.041
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper presents the theoretical results about global Mittag-Leffler stabilization for a class of fractional-order complex-valued memristive neural networks with the designed two types of control rules. As the extension of fractional-order real-valued memristive neural networks, fractional-order complex-valued memristive neural networks have complex-valued states, synaptic weights, and the activation functions. By utilizing the set-valued maps, a generalized fractional derivative inequality as well as fractional-order differential inclusions, several stabilization criteria for global Mittag-Leffler stabilization of fractional-order complex-valued memristive neural networks are established. A numerical example is provided here to illustrate our theoretical results. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码：346 / 362
页数：17
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