Abstract
An algorithm for mutual prediction between time series is used to define an estimator that quantifies the amount of information that is transfered among diffent degrees of freedom of a system. It is presented a numerical example were is possible to discover the direction of greater information flux and a generalized synchronization state. The technique is then aplied to cardiacal rithm and arterial presure data. It is shown that the second transfers more information to the first. Finally, data of frequency and intensity of rain events is also investigated. It is found that there is few information transfer among those time series.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 17-20 |
| Number of pages | 4 |
| Journal | Revista Mexicana de Fisica |
| Volume | 49 |
| Issue number | SUPPL. 3 |
| State | Published - Nov 2003 |
| Externally published | Yes |
Keywords
- General sinchronization
- Information transfer
- Nonlinear interdependence
- Time series analysis
ASJC Scopus subject areas
- Physics and Astronomy(all)