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Further Analysis on Preassigned-time Anti-synchronization of Memristive Inertial BAM Neural Networks
Research Article | Published: 19 November 2025
Journal of Nonlinear Dynamics and Applications Volume 1, Issue 2, 2025: 63-75
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: 63-75

Free to Read | Research Article | 19 November 2025
Further Analysis on Preassigned-time Anti-synchronization of Memristive Inertial BAM Neural Networks
by
Xiao Zhou Xiao Zhou 1 *
Jingrui Hou Jingrui Hou 2
Guodong Zhang Guodong Zhang 1
1 School of Mathematics and Statistics, South-Central Minzu University, Wuhan 430074, China
2 School of Engineering, RMIT University, Melbourne, VIC 3001, Australia
* Corresponding Author: Xiao Zhou, [email protected]
DOI: 10.62762/JNDA.2025.473008
Received: 13 August 2025, Accepted: 17 September 2025, Published: 19 November 2025  
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Abstract
This paper studies the preassigned time anti-synchronization control problem of a class of bidirectional associative memory (BAM) neural networks with inertia terms and memristor characteristics. By constructing a novel Lyapunov-Krasovskii function and combining it with the latest fixed-time stability theory, it strictly proves the sufficient conditions for the system to achieve anti-synchronization within the preassigned time. Numerical simulations further verified the effectiveness and superiority of the method, especially demonstrating higher accuracy and flexibility when dealing with high-order dynamics and memristor-based systems.
Graphical Abstract
Further Analysis on Preassigned-time Anti-synchronization of Memristive Inertial BAM Neural Networks
Keywords
preassigned-time anti-synchronization
non-reduced method
mixed delays
memristive inertial BAM neural networks
Data Availability Statement
Data will be made available on request.
Funding
This work was supported by the National Science Foundation of China under 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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Cite This Article
APA Style
Zhou, X., Hou, J., & Zhang, G. (2025). Further Analysis on Preassigned-time Anti-synchronization of Memristive Inertial BAM Neural Networks. Journal of Nonlinear Dynamics and Applications, 1(2), 63–75. https://doi.org/10.62762/JNDA.2025.473008
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