Global stability analysis of S-asymptotically ω-periodic oscillation in fractional-order cellular neural networks with time variable delays

被引：20
作者：
Qu, Huizhen [1 ]
Zhang, Tianwei [2 ]
Zhou, Jianwen [3 ]
机构：
[1] Guilin Univ Technol Nanning, Sch Basic Sci, Nanning 530001, Guangxi, Peoples R China
[2] Kunming Univ Sci & Technol, Inst Math, Kunming 650051, Yunnan, Peoples R China
[3] Yunnan Univ, Dept Math, Kunming 650091, Yunnan, Peoples R China
来源：
NEUROCOMPUTING | 2020年 / 399卷
基金：
中国国家自然科学基金;
关键词：
Caputo derivative; Mittag-Leffler function; Comparison principle; Laplace transform; MITTAG-LEFFLER STABILITY; DISTRIBUTED DELAYS; MODEL;
D O I：
10.1016/j.neucom.2020.03.005
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A delayed cellular neural networks with Caputo fractional-order derivative has been discussed in this paper. Firstly, the existence and uniqueness of S-asymptotically omega-periodic oscillation of the model are investigated by some important features of Mittag-Leffler functions and contraction mapping principle. Secondly, global asymptotical stability of the model is also studied by using Laplace transform, comparison principle and stability theorem of linear delayed Caputo fractional-order differential equations. Some better results are derived to improve and extend a few existing research findings. The research thoughts in this literature could be applied to research other fractional-order models in neural networks and physical areas. (c) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码：390 / 398
页数：9
相关论文
共 43 条
[1]   Stochastic finite-time stability of reaction-diffusion Cohen-Grossberg neural networks with time-varying delays [J].
Ali, M. Syed ;
Saravanan, S. ;
Palanisamy, L. .
CHINESE JOURNAL OF PHYSICS, 2019, 57 :314-328
[2]   Stability Analysis for a Class of Impulsive Bidirectional Associative Memory (BAM) Neural Networks with Distributed Delays and Leakage Time-Varying Delays [J].
Aouiti, Chaouki ;
Assali, El Abed .
NEURAL PROCESSING LETTERS, 2019, 50 (01) :851-885
[3]   Piecewise asymptotically almost automorphic solutions for impulsive non-autonomous high-order Hopfield neural networks with mixed delays [J].
Aouiti, Chaouki ;
Dridi, Farah .
NEURAL COMPUTING & APPLICATIONS, 2019, 31 (09) :5527-5545
[4]   Oscillation of impulsive neutral delay generalized high-order Hopfield neural networks [J].
Aouiti, Chaouki .
NEURAL COMPUTING & APPLICATIONS, 2018, 29 (09) :477-495
[5]   Pseudo Almost Automorphic Solutions of Recurrent Neural Networks with Time-Varying Coefficients and Mixed Delays [J].
Aouiti, Chaouki ;
M'hamdi, Mohammed Salah ;
Touati, Abderrahmane .
NEURAL PROCESSING LETTERS, 2017, 45 (01) :121-140
[6]   On the exponential stability and periodic solutions of delayed cellular neural networks [J].
Cao, JD ;
Li, Q .
JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS, 2000, 252 (01) :50-64
[7]   Global asymptotical ω-periodicity of a fractional-order non-autonomous neural networks [J].
Chen, Boshan ;
Chen, Jiejie .
NEURAL NETWORKS, 2015, 68 :78-88
[8]   A high-order scheme to approximate the Caputo fractional derivative and its application to solve the fractional diffusion wave equation [J].
Du, Ruilian ;
Yan, Yubin ;
Liang, Zongqi .
JOURNAL OF COMPUTATIONAL PHYSICS, 2019, 376 :1312-1330
[9]   Dynamic analysis of fractional-order predator-prey biological economic system with Holling type II functional response [J].
El-Saka, H. A. A. ;
Lee, Seyeon ;
Jang, Bongsoo .
NONLINEAR DYNAMICS, 2019, 96 (01) :407-416
[10]   Cellular automata as convolutional neural networks [J].
Gilpin, William .
PHYSICAL REVIEW E, 2019, 100 (03)
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