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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]
Volume 1, Issue 2
2025
Received: 08 August 2025
Accepted: 20 September 2025
Published: 17 November 2025
Article Information
Published in
Journal of Nonlinear Dynamics and Applications
Volume/Issue
Volume 1, Issue 2, 2025
Pages
52-62
Cited by
4 (Crossref)
3 (Scopus)
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
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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Cited By (4)
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Ying Qiao, Rukeya Tohti, Binglong Lu, Abdujelil Abdurahman, Haijun Jiang. Internal and boundary control-based fixed-time synchronization for stochastic impulsive reaction-diffusion complex networks.
Chaos, Solitons & Fractals, 2026 , 206 .
[CrossRef] -
Xiao Zhou, Guodong Zhang, Leimin Wang, Qiang Xiao. Novel results on fixed-time stabilization and synchronization for delayed memristive inertial neural networks via aperiodically switching control.
Communications in Nonlinear Science and Numerical Simulation, 2026 , 156 .
[CrossRef] -
Gang Wang, Ikram Mamtimin, Abdujelil Abdurahman. Fixed/Predefined-Time Synchronization for Delayed Memristive Reaction-Diffusion Neural Networks Subject to Stochastic Disturbances.
Axioms, 2026 , 15 (3).
[CrossRef] -
Wei Tian, Guodong Zhang, Guici Chen, Junhao Hu, Shiping Wen. Fixed-time synchronization of delayed memristive reaction-diffusion neural networks via semi-intermittent switching control.
Applied Mathematics and Computation, 2026 , 523 .
[CrossRef]
* Citation data provided by Crossref Cited-by.
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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TY - JOUR
AU - Qiao, Ying
AU - Abudireman, Aminamuhan
AU - Abdurahman, Abdujelil
AU - You, Jingjing
PY - 2025
DA - 2025/11/17
TI - Semi-Intermittent Control Based Fixed/Predefined-Time Synchronization of Spatiotemporal Memristive Neural Networks
JO - Journal of Nonlinear Dynamics and Applications
T2 - Journal of Nonlinear Dynamics and Applications
JF - Journal of Nonlinear Dynamics and Applications
VL - 1
IS - 2
SP - 52
EP - 62
DO - 10.62762/JNDA.2025.841722
UR - https://www.icck.org/article/abs/JNDA.2025.841722
KW - memristor
KW - spatiotemporal neural network
KW - fixed-time/predefined-time synchronization
KW - aperiodic semi-intermittent control
AB - 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.
SN - 3069-6313
PB - Institute of Central Computation and Knowledge
LA - English
ER -
BibTeX Format
Compatible with LaTeX, BibTeX, and other reference managers
@article{Qiao2025SemiInterm,
author = {Ying Qiao and Aminamuhan Abudireman and Abdujelil Abdurahman and Jingjing You},
title = {Semi-Intermittent Control Based Fixed/Predefined-Time Synchronization of Spatiotemporal Memristive Neural Networks},
journal = {Journal of Nonlinear Dynamics and Applications},
year = {2025},
volume = {1},
number = {2},
pages = {52-62},
doi = {10.62762/JNDA.2025.841722},
url = {https://www.icck.org/article/abs/JNDA.2025.841722},
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.},
keywords = {memristor, spatiotemporal neural network, fixed-time/predefined-time synchronization, aperiodic semi-intermittent control},
issn = {3069-6313},
publisher = {Institute of Central Computation and Knowledge}
}
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