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Fixed-time synchronization of delayed memristive reaction-diffusion neural networks via semi-intermittent switching control

Author

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  • Tian, Wei
  • Zhang, Guodong
  • Chen, Guici
  • Hu, Junhao
  • Wen, Shiping

Abstract

This paper investigates the fixed-time synchronization (FXTS) problem for an array of delayed memristive reaction-diffusion neural networks (DMRDNNs) under semi-intermittent switching control (SISC). The proposed model, formulated as a partial differential system, incorporates both temporal and spatial effects, thereby offering broader applicability than models considering only time. Instead of adopting the traditional fixed-time stability criterion, which is commonly used with two power exponent terms, a novel lemma based on a hyperbolic-cosine function is established, containing only one power term. This study improves upon previous related works by achieving a more precise estimation of the settling time (ST). Furthermore, by designing an appropriate controller and applying Green’s formula, the Lyapunov method, and inequality techniques, sufficient conditions are derived to guarantee the FXTS of the drive-response DMRDNNs. Finally, numerical simulations are conducted to validate the effectiveness of the proposed theoretical results.

Suggested Citation

  • Tian, Wei & Zhang, Guodong & Chen, Guici & Hu, Junhao & Wen, Shiping, 2026. "Fixed-time synchronization of delayed memristive reaction-diffusion neural networks via semi-intermittent switching control," Applied Mathematics and Computation, Elsevier, vol. 523(C).
    • Handle: RePEc:eee:apmaco:v:523:y:2026:i:c:s0096300326000780
    DOI: 10.1016/j.amc.2026.130026
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