Nonlinear fractional distributed Halanay inequality and application to neural network systems

被引：7
|
作者：
Kassim, Mohammed D. [1 ]
Tatar, Nasser-eddine [2 ]
机构：
[1] Imam Abdulrahman Bin Faisal Univ, Coll Engn, Dept Basic Engn Sci, POB 1982, Dammam, Saudi Arabia
[2] King Fahd Univ Petr & Minerals, Dept Math & Stat, Interdisciplinary Res Ctr Intelligent Mfg & Robot, Dhahran 31261, Saudi Arabia
来源：
CHAOS SOLITONS & FRACTALS | 2021年 / 150卷
关键词：
Hopfield neural network; Mittag-Leffler stability; Caputo fractional derivative; Fractional Halanay inequality; STABILITY; PERMEABILITY; PREDICTION; OIL;
D O I：
10.1016/j.chaos.2021.111130
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
The standard first order distributed Halanay inequality is generalized in more than one direction. We prove a fractional nonlinear version of this inequality for a large class of kernels which are not necessarily exponentially decaying to zero. This result is used to prove Mittag-Leffler stability of a Hopfiled neural network system with not necessarily globally Lipschitz continuous activation functions. Two classes of important admissible kernels and an example are provided to illustrate our findings. (c) 2021 Elsevier Ltd. All rights reserved.
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收藏
页数：7
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