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Non-linear and linear forecasting of the EEG time series

✍ Scribed by K. J. Blinowska; M. Malinowski


Book ID
104679730
Publisher
Springer-Verlag
Year
1991
Tongue
English
Weight
483 KB
Volume
66
Category
Article
ISSN
0340-1200

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✦ Synopsis


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.


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