Multiple Mittag-Leffler Stability of Fractional-Order Complex-Valued Memristive Neural Networks With Delays

被引:13
|
作者
Shen, Yuanchu [1 ]
Zhu, Song [1 ]
Liu, Xiaoyang [2 ]
Wen, Shiping [3 ]
机构
[1] China Univ Min & Technol, Sch Math, Xuzhou 221116, Jiangsu, Peoples R China
[2] Jiangsu Normal Univ, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China
[3] Univ Technol Sydney, Australian Artificial Intelligence Inst, Ultimo, NSW 2007, Australia
基金
中国国家自然科学基金;
关键词
Biological neural networks; Stability criteria; Circuit stability; Delays; Behavioral sciences; Neurons; Artificial neural networks; Complex-valued neural networks (CVNNs); fractional-order; memristive neural networks; multiple Mittag-Leffler stability; EXPONENTIAL STABILITY; ASSOCIATIVE MEMORY; MULTISTABILITY; SYNCHRONIZATION; BIFURCATION; PASSIVITY;
D O I
10.1109/TCYB.2022.3194059
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 article discusses the coexistence and dynamical behaviors of multiple equilibrium points (Eps) for fractional-order complex-valued memristive neural networks (FCVMNNs) with delays. First, based on the state space partition method, some sufficient conditions are proposed to guarantee that there are multiple Eps in one FCVMNN. Then, the Mittag-Leffler stability of those multiple Eps is proved by using the Lyapunov function. Simultaneously, the enlarged attraction basins are obtained to improve and extend the existing theoretical results in the previous literature. In addition, some existing stability results in the literature are special cases of a new result herein. Finally, two illustrative examples with computer simulations are presented to verify the effectiveness of theoretical analysis.
引用
收藏
页码:5815 / 5825
页数:11
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