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arXiv AI By Zhentao He, Ziwei Wang, Dongrui Wu

KDHNet: A Knowledge-Driven Hybrid Network for Limited-Calibration SSVEP Decoding

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KDHNet is a hybrid network that merges knowledge‑driven analytical filtering with data‑driven deep learning to decode steady‑state visual evoked potentials (SSVEP) from limited calibration data. It uses cascaded task‑discriminant and task‑related component analysis to extract discriminative, reproducible components, then fuses sub‑band weights and a transformer‑based decoder for temporal and spectral representation. Extensive experiments on three public datasets show that KDHNet outperforms existing methods in both intra‑ and inter‑subject settings, especially when calibration data are scarce.

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