Feedback Control for Passivity of Memristor-Based Multiple Weighted Coupled Neural Networks

Bibliographic Details
Title: Feedback Control for Passivity of Memristor-Based Multiple Weighted Coupled Neural Networks
Authors: Xiang-Bo Wang, Hong-An Tang, Qingling Xia, Quanjun Zhao, Gang-Yi Tan
Source: Discrete Dynamics in Nature and Society, Vol 2022 (2022)
Publisher Information: Hindawi Limited, 2022.
Publication Year: 2022
Collection: LCC:Mathematics
Subject Terms: Mathematics, QA1-939
More Details: This paper investigates the passivity of multiple weighted coupled memristive neural networks (MWCMNNs) based on the feedback control. Firstly, a kind of memristor-based coupled neural network model with multiple weights is presented for the first time. Furthermore, a novel passivity criterion for MWCMNNs is established by constructing an appropriate Lyapunov functional and developing a suitable feedback controller. In addition, with the assistance of some inequality techniques, sufficient conditions for ensuring the input strict passivity and output strict passivity of MWCMNNs are derived. Finally, the validity of the theoretical results is verified by a numerical example.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1607-887X
Relation: https://doaj.org/toc/1607-887X
DOI: 10.1155/2022/6920495
Access URL: https://doaj.org/article/61fd56d01800491399cc09a597635c94
Accession Number: edsdoj.61fd56d01800491399cc09a597635c94
Database: Directory of Open Access Journals
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More Details
ISSN:1607887X
DOI:10.1155/2022/6920495
Published in:Discrete Dynamics in Nature and Society
Language:English