Accepted:
04 Feb 2002
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/vol09/das01/ | © Copyright 2002 | |||
| Volume 09 | Received: Accepted: |
08 Sep 2001 04 Feb 2002 |
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Applicability of Lyapunov Exponent in EEG data analysis
Das, A., Das, P. & Roy, A. B. |
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| Abstract | |
| Importance of role of chaos in brain functioning has lead theoretical modelling as well as analysis of electroencephalogram [EEG] data. Two most important chaotic measures are Lyapunov exponent (LE) and dimensional analysis. But the reliability of LE in EEG data analysis has come under question on the basis of the finding that EEG does not represent low dimensional chaos. Here we address this question. We shall at first calculate LE and fractal dimension of EEG data and known Lorenz system. We shall use the surrogating data method to remove nonlinearity of the two datasets. A comparison of values of both the measures for original and its surrogated counterpart is made to find if they can reflect the loss of nonlinearity and hence the loss of information. We find that for EEG data, LE values does not reflect such change, but fractal dimension shows such loss of information. In case of Lorenz data, both the measures reflect the change correctly. So it can be concluded that LEs are not reliable tool in not low dimensional EEG analysis. | |
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Multimedia Links (none) Reference Links Citation Reference Das, A., Das, P. & Roy, A. B. (2002), Applicability of Lyapunov Exponent in EEG data analysis, Complexity International, Volume 09, Paper ID: das01, URL: http://www.complexity.org.au/vol09/das01/ |
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