Synchronization of short memory fractional coupled neural networks with higher-order interactions via novel intermittent control

Dongsheng Yang, Hu Wang, Guojian Ren, Yongguang Yu and Xiao-Li Zhang

Applied Mathematics and Computation, 2025, vol. 497, issue C

Abstract: Due to the fact that higher-order interactions in neural networks significantly enhance the accuracy and depth of network modeling and analysis, this paper investigates the synchronization problem in such networks by employing a novel intermittent control method. Firstly, higher-order interactions in the fractional coupled neural network model are considered, extending the traditional understanding of neural network structures. Based on a designed threshold function, a flexible intermittent controller is introduced. Furthermore, sufficient conditions for achieving network synchronization are provided, ensuring the network reaches a synchronized state under the proposed control method. Alongside these conditions, synchronization criteria are presented to strictly control the synchronization error within a predetermined decay range, guaranteeing the performance meets specific accuracy requirements. Finally, the effectiveness of our innovative intermittent control strategy is demonstrated through two numerical simulations.

Keywords: Fractional; Coupled neural networks; Higher-order interactions; Intermittent control (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:497:y:2025:i:c:s0096300325000906

DOI: 10.1016/j.amc.2025.129363

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