Stability of the Caputo fractional-order inertial neural network with delay-dependent impulses

被引：13
|
作者：
Luo, Lingao [1 ]
Li, Lulu [1 ]
Huang, Wei [1 ]
Cui, Qian [1 ]
机构：
[1] Hefei Univ Technol, Sch Math, Hefei 230009, Peoples R China
来源：
NEUROCOMPUTING | 2023年 / 520卷
基金：
中国国家自然科学基金;
关键词：
Stability; Inertial neural network; Caputo fractional-order derivative; Delayed impulses; MITTAG-LEFFLER STABILITY; EXPONENTIAL STABILITY; DIFFERENTIAL-EQUATIONS; NONLINEAR-SYSTEMS; SYNCHRONIZATION; DYNAMICS; CHAOS;
D O I：
10.1016/j.neucom.2022.11.060
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This article investigates the stability of the Caputo fractional-order inertial neural network (CFOINN) with destabilizing and stabilizing delay-dependent impulses, separately. Firstly, based on average impulsive delay (AID), stability conditions for the Caputo fractional-order (CFO) system with destabilizing and sta-bilizing delay-dependent impulses are separately given by utilizing properties of the CFO derivative. Then, by constructing the Lyapunov function for the CFOINN with delayed impulses, some stability cri-teria are obtained. Finally, numerical examples are presented to verify the effectiveness of the obtained results.(c) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页码：25 / 32
页数：8
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