Feedback Control for Passivity of Memristor-Based Multiple Weighted Coupled Neural Networks. (1st February 2022)
- Record Type:
- Journal Article
- Title:
- Feedback Control for Passivity of Memristor-Based Multiple Weighted Coupled Neural Networks. (1st February 2022)
- Main Title:
- Feedback Control for Passivity of Memristor-Based Multiple Weighted Coupled Neural Networks
- Authors:
- Wang, Xiang-Bo
Tang, Hong-An
Xia, Qingling
Zhao, Quanjun
Tan, Gang-Yi - Other Names:
- Matouk A. E. Academic Editor.
- Abstract:
- Abstract : 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.
- Is Part Of:
- Discrete dynamics in nature and society. Volume 2022(2022)
- Journal:
- Discrete dynamics in nature and society
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-02-01
- Subjects:
- System analysis -- Periodicals
Dynamics -- Periodicals
Chaotic behavior in systems -- Periodicals
Differentiable dynamical systems -- Periodicals
003.05 - Journal URLs:
- https://www.hindawi.com/journals/ddns/ ↗
- DOI:
- 10.1155/2022/6920495 ↗
- Languages:
- English
- ISSNs:
- 1026-0226
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 20869.xml