Kullback-Leibler Approach to Chaotic Time Series
We focus discussion on extracting probability distribution functions (PDFs) from semi-chaotic time series (TS). We wish to ascertain what is the best extraction approach and to such an end we use an extremely well known semiclassical system in its classical limit [1, 2]. Since this systems possesses...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/33586 |
| Acceso en línea: | http://hdl.handle.net/11336/33586 |
| Access Level: | acceso abierto |
| Palabra clave: | Kullback-Leibler-Distance Semiquantum Physics Chaos https://purl.org/becyt/ford/1.3 https://purl.org/becyt/ford/1 |
| Sumario: | We focus discussion on extracting probability distribution functions (PDFs) from semi-chaotic time series (TS). We wish to ascertain what is the best extraction approach and to such an end we use an extremely well known semiclassical system in its classical limit [1, 2]. Since this systems possesses a very rich dynamics, it can safely be regarded as representative of many other physical scenarios. In discussing this ?extraction? problem, we consider the two most natural approaches, namely, i) histograms and ii) the Bandt?Pompe technique. We use the Kullback-Leibler relative entropy to compare the information content of the concomitant PDFs. |
|---|