Model-free classification of multivariate time-series based on epsilon-complexity theory.
FRC Computer Science and Control RAS, Boris Semenovich Darkhovsky, Yuri A. Dubnov, FRC Computer Science and Control RAS, Alexey Yu. Popkov, FRC Computer Science and Control RAS · Transaction Kola Science Centre · 2020
This work is devoted to a new model-free approach to a problem of binary classification of multivariate time-series. The approach is based on the original theory of epsilon-complexity which allows almost every mapping that satisfies Hoelder condition, be characterized by a pair of real numbers –complexity coefficients. Thus we can form a feature space in which a classification problem can be formulated and solved. We provide an example of classification of real EEG signals.