Finite-time parameter identification of fractional-order time-varying delay neural networks based on synchronization-Reference-Cited by-同舟云学术

Finite-time parameter identification of fractional-order time-varying delay neural networks based on synchronization

Published:2023-03-01 Issue:3 Volume:33 Page:
ISSN:1054-1500
Container-title:Chaos: An Interdisciplinary Journal of Nonlinear Science
language:en
Short-container-title:

Author:

Yang Fan¹^ORCID,Wang Wen¹^ORCID,Li Lixiang²^ORCID,Zheng Mingwen¹^ORCID,Zhang Yanping¹^ORCID,Liang Zhenying¹^ORCID

Affiliation:

1. School of Mathematics and Statistics, Shandong University of Technology 1 , Zibo 255000, China

2. Information Security Center, State Key Laboratory of Networking and Switching Technology, and National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications 2 , Beijing 100086, China

Abstract

We research the finite-time parameter identification of fractional-order time-varying delay neural networks (FTVDNNs) based on synchronization. First, based on the fractional-order Lyapunov stability theorem and feedback control idea, we construct a synchronous controller and some parameter update rules, which accomplish the synchronization of the drive-response FTVDNNs and complete the identification of uncertain parameters. Second, the theoretical analysis of the synchronization method is carried out, and the stable time is calculated. Finally, we give two examples for simulation verification. Our method can complete the synchronization of the FTVDNNs in finite time and identify uncertain parameters while synchronizing.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

National Key Research and Development Program of China

Publisher

AIP Publishing

Subject

Applied Mathematics,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

Link

https://pubs.aip.org/aip/cha/article-pdf/doi/10.1063/5.0137598/16791399/033146_1_online.pdf

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