A general extractor for coherent patterns across time-frequency measurements
TokEye is a self-supervised framework that automatically extracts coherent and transient modes from noisy time-frequency data across various sensors. It uses signal taxonomy and deep learning, including U-Nets, to separate these signals from background noise in real time. This enables automated database creation for advanced plasma control.