Novel methods to global Mittag-Leffler stability of delayed fractional-order quaternion-valued neural networks.

Fractional-order Leakage delay Mittag-Leffler stability Quaternion-valued neural networks Time-varying delay

Journal

Neural networks : the official journal of the International Neural Network Society
ISSN: 1879-2782
Titre abrégé: Neural Netw
Pays: United States
ID NLM: 8805018

Informations de publication

Date de publication:
Oct 2021
Historique:
received: 11 03 2021
revised: 21 05 2021
accepted: 05 07 2021
pubmed: 20 7 2021
medline: 25 11 2021
entrez: 19 7 2021
Statut: ppublish

Résumé

In this paper, a type of fractional-order quaternion-valued neural networks (FOQVNNs) with leakage and time-varying delays is established to simulate real-world situations, and the global Mittag-Leffler stability of the system is investigated by using the non-decomposition method. First, to avoid decomposing the system into two complex-valued systems or four real-valued systems, a new sign function for quaternion numbers is introduced based on the ones for real and complex numbers. And two novel lemmas for quaternion-valued sign function and Caputo fractional derivative are established in quaternion domain, which are used to investigate the stability of FOQVNNs. Second, a concise and flexible quaternion-valued state feedback controller is directly designed and a novel 1-norm Lyapunov function composed of the absolute values of real and imaginary parts is established. Then, based on the designed quaternion-valued state feedback controller and the proposed lemmas, some sufficient conditions are given to ensure the global Mittag-Leffler stability of the system. Finally, a numerical simulation is given to verify the theoretical results.

Identifiants

pubmed: 34280693
pii: S0893-6080(21)00268-9
doi: 10.1016/j.neunet.2021.07.005
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

500-508

Informations de copyright

Copyright © 2021 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Hongyun Yan (H)

Faculty of Science, Beijing University of Technology, Beijing 100124, China. Electronic address: hyyan@emails.bjut.edu.cn.

Yuanhua Qiao (Y)

Faculty of Science, Beijing University of Technology, Beijing 100124, China. Electronic address: qiaoyuanhua@bjut.edu.cn.

Lijuan Duan (L)

Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China. Electronic address: ljduan@bjut.edu.cn.

Jun Miao (J)

School of Computer Science, Beijing Information Science and Technology University, Beijing 100101, China. Electronic address: jmiao@bistu.edu.cn.

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Classifications MeSH