AI RESEARCH
Personalized Spiking Neural Networks with Ferroelectric Synapses for EEG Signal Processing
arXiv CS.AI
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ArXi:2601.00020v3 Announce Type: replace-cross Electroencephalography (EEG)-based brain-computer interfaces (BCIs) are strongly affected by non-stationary neural signals that vary across sessions and individuals, limiting the generalization of subject-agnostic models and motivating adaptive and personalized learning on resource-constrained platforms.