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Volume 1, Issue 2, Journal of Nonlinear Dynamics and Applications
Volume 1, Issue 2, 2025
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Journal of Nonlinear Dynamics and Applications, Volume 1, Issue 2, 2025: 52-62

Free to Read | Research Article | 17 November 2025
Semi-Intermittent Control Based Fixed/Predefined-Time Synchronization of Spatiotemporal Memristive Neural Networks
1 College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, China
* Corresponding Author: Abdujelil Abdurahman, [email protected]
Received: 08 August 2025, Accepted: 20 September 2025, Published: 17 November 2025  
Abstract
This article addresses the fixed-time (FXT) and predefined-time (PDT) synchronization issues of spatiotemporal memristive neural networks (MNNs). First, an aperiodic semi-intermittent control (ASIC) scheme is introduced to reduce the control costs. Then, some novel FXT/PDT synchronization criteria are obtained by using Guass's divergence theorem and by Lyapunov {functional method}. Finally, the feasibility of the theoretical results is confirmed through numerical simulations.

Graphical Abstract
Semi-Intermittent Control Based Fixed/Predefined-Time Synchronization of Spatiotemporal Memristive Neural Networks

Keywords
memristor
spatiotemporal neural network
fixed-time/predefined-time synchronization
aperiodic semi-intermittent control

Data Availability Statement
Data will be made available on request.

Funding
This work was supported the Outstanding Youth Program of Xinjiang, China under Grant 2022D01E10 and the National Natural Science Foundation of China under Grant 62266042.

Conflicts of Interest
The authors declare no conflicts of interest.

Ethical Approval and Consent to Participate
Not applicable.

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Cite This Article
APA Style
Qiao, Y., Abudireman, A., Abdurahman, A., & You, J. (2025). Semi-Intermittent Control Based Fixed/Predefined-Time Synchronization of Spatiotemporal Memristive Neural Networks. Journal of Nonlinear Dynamics and Applications, 1(2), 52–62. https://doi.org/10.62762/JNDA.2025.841722

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