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Rethinking EEG Spatial Super-Resolution as Dynamic State Decomposition and Filtering
EEG spatial super-resolution aims to recover high-density neural signals from sparse electrode observations. Existing methods have achieved substantial progress through spatial modeling, generative reconstruction, and temporal representation learning. However, the current EEG state contains two diff
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