Nonlinear data analysis of experimental (EEG) data and comparison with theoretical (ANN) data
Version of Record online: 10 JUN 2002
Copyright © 2002 Wiley Periodicals, Inc.
Volume 7, Issue 3, pages 30–40, January/February 2002
How to Cite
Das, A., Das, P. and Roy, A. B. (2002), Nonlinear data analysis of experimental (EEG) data and comparison with theoretical (ANN) data. Complexity, 7: 30–40. doi: 10.1002/cplx.10024
- Issue online: 10 JUN 2002
- Version of Record online: 10 JUN 2002
- Manuscript Revised: 7 JAN 2002
- Manuscript Accepted: 7 JAN 2002
- Manuscript Received: 25 AUG 2001
- Lyapunov exponents;
- fractal and correlation dimension;
- surrogate data
In this article, nonlinear dynamical tools such as largest Lyapunov exponents (LE), fractal dimension, correlation dimension, pointwise correlation dimension will be used to analyze electroencephalogram (EEG) data obtained from healthy young subjects with eyes open and eyes closed condition with the view to compare brain complexity under this two condition. Results of similar calculations from some earlier works will be produced for comparison with present results. Also, a brief report on difference of opinion among coworkers regarding such tools will be reported; particularly applicability of LE will be reviewed. The issue of nonlinearity will be addressed by using surrogate data technique. We have extracted another data set that represented chaotic state of the system considered in our earlier work of mathematical modeling of artificial neural network. We further attempt to compare results to find nature of chaos arising from such theoretical models. © 2002 Wiley Periodicals, Inc.