This paper focuses on the synchronization of fractional-order reaction–diffusion neural networks (FORDNN) under sampling event-triggered iterative learning control. A Dα-type iterative learning protocol of complete synchronization is proposed, which combines the advantages of both event-triggered control and sampling iterative learning control. Using mathematical tools, sufficient conditions for synchronization are derived. A numerical simulation example is provided to confirm the effectiveness of the analysis.
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Dai et al. (2025) studied this question.
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