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Mathematics
Volume 13
Issue 22
10.3390/math13223592
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Fixed-Time Synchronization of Memristive Inertial BAM Neural Networks via Aperiodic Switching Control

by
Xiao Zhou
1,
Jing Han
2,
Yan Li
3 and
Guodong Zhang
1,*
1
School of Mathematics and Statistics, South-Central Minzu University, Wuhan 430074, China
2
School of Information Engineering, Wuhan Business University, Wuhan 430010 , China
3
College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
*
Author to whom correspondence should be addressed.
Mathematics 2025, 13(22), 3592; https://doi.org/10.3390/math13223592 (registering DOI)
Submission received: 17 September 2025 / Revised: 31 October 2025 / Accepted: 6 November 2025 / Published: 9 November 2025
(This article belongs to the Special Issue Finite-Time/Fixed-Time Stability and Control of Dynamical Systems)
Versions Notes

Abstract

This paper investigates the fixed-time stabilization and synchronization of a class of memristor inertial BAM neural networks with mixed delays using a non-order reduction method. By constructing a Lyapunov function and leveraging novel fixed-time stability lemmas, we design an aperiodic switching controller that addresses the inflexibility of traditional periodic control in high-order systems. Theoretical analysis proves that the controller ensures system states converge to equilibrium within a fixed time, independent of initial conditions. The inclusion of mixed delays further enhances the model’s practicality. Notably, the proposed method is applied to secure communication, demonstrating its capability to protect information transmission in realworld scenarios. Numerical simulations validate the effectiveness of the approach, with secure communication experiments specifically confirming its encryption potential. This work bridges theoretical control design with critical cybersecurity applications.
Keywords: memristive inertial BAM neural networks; non-reduced method; mixed delays; fixed-time stabilization; fixed-time synchronization; aperiodically switching strategy memristive inertial BAM neural networks; non-reduced method; mixed delays; fixed-time stabilization; fixed-time synchronization; aperiodically switching strategy

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MDPI and ACS Style

Zhou, X.; Han, J.; Li, Y.; Zhang, G. Fixed-Time Synchronization of Memristive Inertial BAM Neural Networks via Aperiodic Switching Control. Mathematics 2025, 13, 3592. https://doi.org/10.3390/math13223592

AMA Style

Zhou X, Han J, Li Y, Zhang G. Fixed-Time Synchronization of Memristive Inertial BAM Neural Networks via Aperiodic Switching Control. Mathematics. 2025; 13(22):3592. https://doi.org/10.3390/math13223592

Chicago/Turabian Style

Zhou, Xiao, Jing Han, Yan Li, and Guodong Zhang. 2025. "Fixed-Time Synchronization of Memristive Inertial BAM Neural Networks via Aperiodic Switching Control" Mathematics 13, no. 22: 3592. https://doi.org/10.3390/math13223592

APA Style

Zhou, X., Han, J., Li, Y., & Zhang, G. (2025). Fixed-Time Synchronization of Memristive Inertial BAM Neural Networks via Aperiodic Switching Control. Mathematics, 13(22), 3592. https://doi.org/10.3390/math13223592

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