Biological Cybernetics

, Volume 66, Issue 2, pp 159–165

Non-linear and linear forecasting of the EEG time series

  • K. J. Blinowska
  • M. Malinowski

DOI: 10.1007/BF00243291

Cite this article as:
Blinowska, K.J. & Malinowski, M. Biol. Cybern. (1991) 66: 159. doi:10.1007/BF00243291


The method of non-linear forecasting of time series was applied to different simulated signals and EEG in order to check its ability of distinguishing chaotic from noisy time series. The goodness of prediction was estimated, in terms of the correlation coefficient between forecasted and real time series, for non-linear and autoregressive (AR) methods. For the EEG signal both methods gave similar results. It seems that the EEG signal, in spite of its chaotic character, is well described by the AR model.

Copyright information

© Springer-Verlag 1991

Authors and Affiliations

  • K. J. Blinowska
    • 1
  • M. Malinowski
    • 1
  1. 1.Laboratory of Medical Physics, Warsaw UniversityWarszawaPoland

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