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.
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页码：607 / 621
页数：14
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