STOCHASTIC PROCESSES OF DEMARKQVIZATION AND MARKOVIZATIQN IN CHAOTIC SIGNALS OF THE HUMAN BRAIN ELECTRIC ACTIVITY FROM EEGs AT EPILEPSY

摘要

We study the stochastic processes of markovization and demarkovization in chaotic signals of human electroencephalograms (EEGs) at epilepsy using various measures of demarkovization and markovization, namely, the statistical spectrum of a non-Markovity parameter, power spectra of the time correlation function and memory functions of junior orders, and local relaxation and kinetic parameters. The results demonstrate the superiority of the new measures in comparison to the traditional nonlinear measures. We conclude that the applied measures are more appropriate for the quantification of markovization and demarkovization in EEG data and the prediction of epilepsy seizure.