Asymptotically stable high-order neutral cellular neural networks with proportional delays and D operators

被引:79
作者
Huang, Chuangxia [1 ,2 ]
Su, Renli [1 ,2 ]
Cao, Jinde [3 ]
Xiao, Songlin [4 ]
机构
[1] Changsha Univ Sci & Technol, Dept Appl Math, Changsha, Peoples R China
[2] Hunan Prov Key Lab Math Modeling & Anal Engn, Changsha 410114, Peoples R China
[3] Southeast Univ, Sch Math, Nanjing 210096, Peoples R China
[4] Putian Univ, Sch Math & Finance, Putian 351100, Peoples R China
基金
中国国家自然科学基金;
关键词
Neutral cellular neural networks; Proportional delay; Asymptotic stability; D operator; ALMOST-PERIODIC SOLUTIONS; NICHOLSONS BLOWFLIES MODEL; LIMIT-CYCLES; STABILITY; SYSTEMS;
D O I
10.1016/j.matcom.2019.06.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper aims to deal with the asymptotic stability of high-order neutral cellular neural networks (HNCNNs) incorporating proportional delays and D operators. Employing Lyapunov method, inequality technique and concise mathematical analysis proof, sufficient criteria on the global exponential asymptotical stability of the proposed HNCNNs are obtained. The main results provide us some light for designing stable HNCNNs and complement some earlier publications. In addition, simulations show that the theoretical convergence is in excellent agreement with the numerically observed behavior. (C) 2019 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:127 / 135
页数:9
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