Abstract
A classic problem in physics is the analysis of highly nonsta- tionary time series that t ypically exhibit long-range correlations. Here w e tested the hypothesis that the scaling exponents of the dynamics of sleeping EEG have more? stable pattern than those of waken EEG by analyzing its fluctuations. We calculated the modified fluctuations of EEG stage with detrended fluctuation analysis(DFA). DFA is very useful to detect a long-range1 correlation in the time-series. Wc found a scaling exponent of sleeping stage is larger than that of waken. © Springer-Verlag Berlin Heidelberg 2001.
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CITATION STYLE
Lee, J. M., Kirn, D. J., Kim, I. Y., & Kim, S. I. (2001). Analysis of scaling exponents of waken and sleeping stage in EEG. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2084 LNCS, pp. 450–456). Springer Verlag. https://doi.org/10.1007/3-540-45720-8_53
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