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New Exponential Function Based Fixed/Preassigned-Time Synchronization for A Kind of Neural Networks with Time-Varying Delays
1
School of Mathematics and Statistics, South-Central Minzu University, Wuhan 430074, China
2
Department of Mathematics, Bharathiar University, Coimbatore, Tamil Nadu, India
* Corresponding Author:
Guodong Zhang,
[email protected]
Volume 1, Issue 1
2025
Received: 07 August 2025
Accepted: 22 August 2025
Published: 29 August 2025
Article Information
Published in
Journal of Nonlinear Dynamics and Applications
Volume/Issue
Volume 1, Issue 1, 2025
Pages
26-35
Cited by
5 (Crossref)
6 (Scopus)
Abstract
This paper investigates a class of neural networks (NNs) with time-varying delays. At first, based on the general exponential function and by using inequality techniques, we establish novel lemmas addressing fixed/preassigned-time synchronization for such NNs. Then, by employing these derived lemmas and designing two effective feedback controllers, we systematically study the fixed-time synchronization (FTS) and preassigned-time synchronization (PRTS) problems of delayed NNs. In addition, the settling-time estimation in our fixed-time stability lemma expresses superior accuracy compared to existing results in previous related works, which can all be viewed as special cases of this paper. Finally, numerical simulations demonstrate the validity and practicality of the theoretical findings.
Graphical Abstract
Keywords
neural networks (NNs)
fixed-time synchronization (FTS)
preassigned-time synchronization (PRTS)
feedback control
time-varying delays
Data Availability Statement
Data will be made available on request.
Funding
This work was supported by the National Science Foundation of China under Grant 61976228 and Grant 62476292, and the Fundamental Research Funds for Central University of South-Central Minzu University under Grant CZQ24020.
Conflicts of Interest
The authors declare no conflicts of interest.
Ethical Approval and Consent to Participate
Not applicable.
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Cited By (5)
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Applied Mathematical Modelling, 2026 , 154 .
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Weizhe Xu, Song Zhu. Unified analysis of stability and dissipativity for inertial memristive multidimensional-valued neural networks with time-varying delays via non-reduced order method.
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[CrossRef] -
Leimin Wang, Zheng Zhou, Guanghui Jiang, Qingyi Wang, Zhouchao Wei. Fixed-/Preassigned-time synchronization of differential-dimensional chaotic systems with stochastic disturbances.
Applied Mathematics and Computation, 2026 , 519 .
[CrossRef] -
Yinjie Qian, Xuyan Jiang, Yuanhua Qiao. New results on fixed/preassigned-time synchronization of spatiotemporal memristive fuzzy neural networks with time delays.
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[CrossRef]
* Citation data provided by Crossref Cited-by.
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APA Style
Zhang, G., & Rakkiyappan, R. (2025). New Exponential Function Based Fixed/Preassigned-Time Synchronization for A Kind of Neural Networks with Time-Varying Delays. Journal of Nonlinear Dynamics and Applications, 1(1), 26–35. https://doi.org/10.62762/JNDA.2025.937806
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TY - JOUR AU - Zhang, Guodong AU - Rakkiyappan, Rajan PY - 2025 DA - 2025/08/29 TI - New Exponential Function Based Fixed/Preassigned-Time Synchronization for A Kind of Neural Networks with Time-Varying Delays JO - Journal of Nonlinear Dynamics and Applications T2 - Journal of Nonlinear Dynamics and Applications JF - Journal of Nonlinear Dynamics and Applications VL - 1 IS - 1 SP - 26 EP - 35 DO - 10.62762/JNDA.2025.937806 UR - https://www.icck.org/article/abs/JNDA.2025.937806 KW - neural networks (NNs) KW - fixed-time synchronization (FTS) KW - preassigned-time synchronization (PRTS) KW - feedback control KW - time-varying delays AB - This paper investigates a class of neural networks (NNs) with time-varying delays. At first, based on the general exponential function and by using inequality techniques, we establish novel lemmas addressing fixed/preassigned-time synchronization for such NNs. Then, by employing these derived lemmas and designing two effective feedback controllers, we systematically study the fixed-time synchronization (FTS) and preassigned-time synchronization (PRTS) problems of delayed NNs. In addition, the settling-time estimation in our fixed-time stability lemma expresses superior accuracy compared to existing results in previous related works, which can all be viewed as special cases of this paper. Finally, numerical simulations demonstrate the validity and practicality of the theoretical findings. SN - 3069-6313 PB - Institute of Central Computation and Knowledge LA - English ER -
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@article{Zhang2025New,
author = {Guodong Zhang and Rajan Rakkiyappan},
title = {New Exponential Function Based Fixed/Preassigned-Time Synchronization for A Kind of Neural Networks with Time-Varying Delays},
journal = {Journal of Nonlinear Dynamics and Applications},
year = {2025},
volume = {1},
number = {1},
pages = {26-35},
doi = {10.62762/JNDA.2025.937806},
url = {https://www.icck.org/article/abs/JNDA.2025.937806},
abstract = {This paper investigates a class of neural networks (NNs) with time-varying delays. At first, based on the general exponential function and by using inequality techniques, we establish novel lemmas addressing fixed/preassigned-time synchronization for such NNs. Then, by employing these derived lemmas and designing two effective feedback controllers, we systematically study the fixed-time synchronization (FTS) and preassigned-time synchronization (PRTS) problems of delayed NNs. In addition, the settling-time estimation in our fixed-time stability lemma expresses superior accuracy compared to existing results in previous related works, which can all be viewed as special cases of this paper. Finally, numerical simulations demonstrate the validity and practicality of the theoretical findings.},
keywords = {neural networks (NNs), fixed-time synchronization (FTS), preassigned-time synchronization (PRTS), feedback control, time-varying delays},
issn = {3069-6313},
publisher = {Institute of Central Computation and Knowledge}
}
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