Multistability of Fractional-Order Neural Networks With Unbounded Time-Varying Delays

被引：26

作者：

Zhang, Fanghai ^{[1
,2
]}

Zeng, Zhigang ^{[1
,3
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Peoples R China

[2] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430074, Peoples R China

[3] Educ Minist China, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Peoples R China

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | 2021年 / 32卷 / 01期

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

Delays; Stability criteria; Biological neural networks; Asymptotic stability; Numerical stability; Attraction; fractional-order neural networks (FONNs); Mittag-Leffler stability; multistability; unbounded time-varying delays; MITTAG-LEFFLER STABILITY; EXPONENTIAL STABILITY; ACTIVATION FUNCTIONS; GLOBAL STABILITY;

D O I：

10.1109/TNNLS.2020.2977994

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This article addresses the multistability and attraction of fractional-order neural networks (FONNs) with unbounded time-varying delays. Several sufficient conditions are given to ensure the coexistence of equilibrium points (EPs) of FONNs with concave-convex activation functions. Moreover, by exploiting the analytical method and the property of the Mittag-Leffler function, it is shown that the multiple Mittag-Leffler stability of delayed FONNs is derived and the obtained criteria do not depend on differentiable time-varying delays. In particular, the criterion of the Mittag-Leffler stability can be simplified to M-matrix. In addition, the estimation of attraction basin of delayed FONNs is studied, which implies that the extension of attraction basin is independent of the magnitude of delays. Finally, three numerical examples are given to show the validity of the theoretical results.

引用

页码：177 / 187

页数：11

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