Finite-Time Stability for Caputo–Katugampola Fractional-Order Time-Delayed Neural Networks

被引：0
|
作者：
Assaad Jmal
Abdellatif Ben Makhlouf
A. M. Nagy
Omar Naifar
机构：
[1] Sfax University,Control and Energy Management Laboratory, National School of Engineering
[2] Jouf University,Department of Mathematics, College of Science
[3] Kuwait University,Department of Mathematics, Faculty of Science
[4] Benha University,Department of Mathematics, Faculty of Science
来源：
Neural Processing Letters | 2019年 / 50卷
关键词：
Fractional-order calculus; Neural networks; Finite-time stability; Caputo–Katugampola derivative;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, an original scheme is presented, in order to study the finite-time stability of the equilibrium point, and to prove its existence and uniqueness, for Caputo–Katugampola fractional-order neural networks, with time delay. The proposed scheme uses a newly introduced fractional derivative concept in the literature, which is the Caputo–Katugampola fractional derivative. The effectiveness of the theoretical results is shown through simulations for two numerical examples.
引用
收藏
页码：607 / 621
页数：14
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