Exponential stability and synchronization of Memristor-based fractional-order fuzzy cellular neural networks with multiple delays

被引：35
|
作者：
Yao, Xueqi [1 ,2 ]
Liu, Xinzhi [2 ]
Zhong, Shouming [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Peoples R China
[2] Univ Waterloo, Dept Appl Math, Waterloo, ON N2L 3G1, Canada
来源：
NEUROCOMPUTING | 2021年 / 419卷
关键词：
Fuzzy cellular neural networks; Fractional-order; Memristor; Multiple delays; Exponential stability; FINITE-TIME STABILITY; NONLINEAR-SYSTEMS;
D O I：
10.1016/j.neucom.2020.08.057
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The stability and synchronization problems are addressed in this study for the memristor-based fractional-order fuzzy cellular neural networks with multiple delays. By using the Laplace transform method, fractional-order calculus approach and the method of complex function, three exponential sta-bility criteria are derived. Compared with the existing results of the above system, the novel exponentially stable and synchronization conditions are first proposed. The obtained results can be applied not only to fractional-order systems, but also to integer-order systems. A two-dimension example and a three-dimension example and a practical example are given to illustrate the validity and merits. (c) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码：239 / 250
页数：12
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