  Dynamical Component Analysis (DyCA) is a recently-proposed method to detect
projection vectors to reduce the dimensionality of multi-variate deterministic
datasets. It is based on the solution of a generalized eigenvalue problem and
therefore straight forward to implement. DyCA is introduced and applied to EEG
data of epileptic seizures. The obtained eigenvectors are used to project the
signal and the corresponding trajectories in phase space are compared with PCA
and ICA-projections. The eigenvalues of DyCA are utilized for seizure detection
and the obtained results in terms of specificity, false discovery rate and miss
rate are compared to other seizure detection algorithms.

Signal Processing;Machine Learning;Chaotic Dynamics