| dc.creator | Martín, María Teresa | |
| dc.creator | Plastino, Ángel Luis | |
| dc.creator | Vampa, Victoria | |
| dc.date | 2014 | |
| dc.date | 2019-11-06T14:12:30Z | |
| dc.identifier | http://sedici.unlp.edu.ar/handle/10915/85041 | |
| dc.identifier | issn:1099-4300 | |
| dc.description | The development of methods for time series analysis and prediction has always been and continues to be an active area of research. In this work, we develop a technique for modelling chaotic time series in parametric fashion. In the case of tonic-clonic epileptic electroencephalographic (EEG) analysis, we show that appropriate information theory tools provide valuable insights into the dynamics of neural activity. Our purpose is to demonstrate the feasibility of the maximum entropy principle to anticipate tonic-clonic seizure in patients with epilepsy. | |
| dc.description | Facultad de Ciencias Exactas | |
| dc.description | Instituto de Física La Plata | |
| dc.description | Facultad de Ingeniería | |
| dc.format | application/pdf | |
| dc.format | 4603-4611 | |
| dc.language | en | |
| dc.rights | http://creativecommons.org/licenses/by/3.0/ | |
| dc.rights | Creative Commons Attribution 3.0 Unported (CC BY 3.0) | |
| dc.subject | Ciencias Exactas | |
| dc.subject | Ingeniería | |
| dc.subject | Maximum entropy | |
| dc.subject | Pseudo-inverse approach | |
| dc.subject | Tonic-clonic EEG transition | |
| dc.title | A maximum entropy approach for predicting epileptic tonic-clonic seizure | |
| dc.type | Articulo | |
| dc.type | Articulo | |
