| dc.creator | Olivares, Felipe | |
| dc.creator | Zunino, Luciano José | |
| dc.creator | Soriano, Miguel C. | |
| dc.creator | Pérez, Darío G. | |
| dc.date | 2019-10-24 | |
| dc.date | 2021-09-07T14:38:58Z | |
| dc.date.accessioned | 2023-07-15T03:14:25Z | |
| dc.date.available | 2023-07-15T03:14:25Z | |
| dc.identifier | http://sedici.unlp.edu.ar/handle/10915/124294 | |
| dc.identifier | issn:2470-0045 | |
| dc.identifier | issn:2470-0053 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/7464959 | |
| dc.description | In this paper, we introduce a model to describe the decay of the number of unobserved ordinal patterns as a function of the time series length in noisy chaotic dynamics. More precisely, we show that a stretched exponential model fits the decay of the number of unobserved ordinal patterns for both discrete and continuous chaotic systems contaminated with observational noise, independently of the noise level and the sampling time. Numerical simulations, obtained from the logistic map and the x coordinate of the Lorenz system, both operating in a totally chaotic dynamics were used as test beds. In addition, we contrast our results with those obtained from pure stochastic dynamics. The fitting parameters, namely, the stretching exponent and the characteristic decay rate, are used to distinguish whether the dynamical nature of the data sequence is stochastic or chaotic. Finally, the analysis of experimental records associated with the hyperchaotic pulsations of an optoelectronic oscillator allows us to illustrate the applicability of the proposed approach in a practical context. | |
| dc.description | Facultad de Ingeniería | |
| dc.description | Centro de Investigaciones Ópticas | |
| dc.format | application/pdf | |
| dc.language | en | |
| dc.rights | http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
| dc.rights | Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) | |
| dc.subject | Ingeniería | |
| dc.subject | Física | |
| dc.subject | chaotic dynamics | |
| dc.subject | time series length | |
| dc.subject | unobserved ordinal patterns | |
| dc.subject | noise | |
| dc.title | Unraveling the decay of the number of unobserved ordinal patterns in noisy chaotic dynamics | |
| dc.type | Articulo | |
| dc.type | Articulo | |
