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Dejin Zhao

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Open access Jul 2026

Data-driven adaptive gain tuning for the augmented homogeneous differentiator

This paper presents an adaptive-gain AHD in which a network combining convolutional, recurrent, and attention layers is trained offline and deployed online to predict, from a short window of the raw noisy signal, the smallest gain that meets a prescribed velocity-accuracy target.

Xi Chen, Shanhai Jin, Dejin Zhao et al. · 0 citations