Fractional Delay Time Embedding of EEG Signals into High Dimensional Phase Space

We propose a method for reconstruction of the high-dimensional phase space of the electroencephalography (EEG) signal. The method is based on the selection of positive trajectories from the phase space, distance-adaptive sampling of the negative trajectories from the phase space, classification of trajectories in the phase space, and reconstruction of a fuzzy state of the signal for classification of EEG signals. Index Terms--Adaptive classification, delay time embedding, phase space, landmark signal, EEG, BCI.