Synchronization of fractional-order reaction-diffusion neural networks via mixed boundary control

被引：15
作者：
Sun, Yuting [1 ]
Hu, Cheng [1 ]
Yu, Juan [1 ]
Shi, Tingting [1 ]
机构：
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830017, Xinjiang, Peoples R China
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2023年 / 450卷
基金：
中国国家自然科学基金;
关键词：
Synchronization; Fractional-order; Reaction-diffusion; Boundary control; Neural network; MITTAG-LEFFLER STABILIZATION; TIME-VARYING DELAYS; GLOBAL SYNCHRONIZATION; COMPLEX NETWORKS; STATE; TRANSPORT; BEHAVIOR; MODEL;
D O I：
10.1016/j.amc.2023.127982
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This article studies the synchronization issue of fractional reaction-diffusion neural net-works (FRDNNs) with time delay and mixed boundary condition . First, a novel bound-ary controller with constant-valued gain is designed, which only relies on the boundary state information. Subsequently, by virtue of Lyapunov direct technique and LMI approach, the Mittag-Leffler synchronization conditions are established. Besides, to effectively reg-ulate the control gain, a fractional-order adaptive boundary controller is developed and the adaptive synchronization of FRDNNs is rigorously analyzed. Note that, the above con-trol strategies are also workable for traditional integer-order reaction-diffusion neural net-works. The developed theoretical analysis is supported eventually via a numerical example.(c) 2023 Elsevier Inc. All rights reserved.
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页数：15
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