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

Author

Listed:
  • Yang, Dongsheng
  • Wang, Hu
  • Ren, Guojian
  • Yu, Yongguang
  • Zhang, Xiao-Li

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.

Suggested Citation

  • Yang, Dongsheng & Wang, Hu & Ren, Guojian & Yu, Yongguang & Zhang, Xiao-Li, 2025. "Synchronization of short memory fractional coupled neural networks with higher-order interactions via novel intermittent control," Applied Mathematics and Computation, Elsevier, vol. 497(C).
    • Handle: RePEc:eee:apmaco:v:497:y:2025:i:c:s0096300325000906
    DOI: 10.1016/j.amc.2025.129363
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    References listed on IDEAS

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