Abstract
The possibility of using the permutation entropy (PE) to detect dynamical changes in a complex time series was discussed. It was shown that PE can be used to detect bifurcations in model systems. It was also shown that permutation entropy can be effectively used to detect qualitative and quantitative dynamical changes. The results were illustrated on two model systems as well as on clinically characterized brain wave data.
| Original language | English |
|---|---|
| Article number | 046217 |
| Pages (from-to) | 046217-1-046217-7 |
| Journal | Physical Review E - Statistical, Nonlinear, and Soft Matter Physics |
| Volume | 70 |
| Issue number | 4 2 |
| DOIs | |
| State | Published - Oct 2004 |
Funding
The authors thank Professor Sackellares of the Shands Hospital at the University of Florida for kindly providing them with the EEG data and Ms. Hui Liu for preparing the data. V.P. was partially supported by the Division of Material Sciences and Engineering, DOE Office of Basic Sciences. ORNL is operated for the DOE under Contract No. DE-AC05–00OR22725 with UT-Battele, LLC.