期刊论文详细信息
Entropy
Selection of Embedding Dimension and Delay Time in Phase Space Reconstruction via Symbolic Dynamics
JoseMiguel Rodríguez1  ManuelRuiz Marín1  Mariano Matilla-García2  Isidro Morales3 
[1] Departamento Metodos Cuantitativos, Ciencias Juridicas y Lenguas Modernas, Universidad Politecnica de Cartagena, 30201 Cartagena, Spain;Facultad de Economicas y Empresariales, Universidad Nacional de Educación a Distancia (UNED), 28050 Madrid, Spain;Telefónica, 28040 Madrid, Spain;
关键词: symbolic analysis;    symbolic entropy;    delay time selection;    dynamic reconstruction;   
DOI  :  10.3390/e23020221
来源: DOAJ
【 摘 要 】

The modeling and prediction of chaotic time series require proper reconstruction of the state space from the available data in order to successfully estimate invariant properties of the embedded attractor. Thus, one must choose appropriate time delay τ* and embedding dimension p for phase space reconstruction. The value of τ* can be estimated from the Mutual Information, but this method is rather cumbersome computationally. Additionally, some researchers have recommended that τ* should be chosen to be dependent on the embedding dimension p by means of an appropriate value for the time delay τw=(p1)τ*, which is the optimal time delay for independence of the time series. The C-C method, based on Correlation Integral, is a method simpler than Mutual Information and has been proposed to select optimally τw and τ*. In this paper, we suggest a simple method for estimating τ* and τw based on symbolic analysis and symbolic entropy. As in the C-C method, τ* is estimated as the first local optimal time delay and τw as the time delay for independence of the time series. The method is applied to several chaotic time series that are the base of comparison for several techniques. The numerical simulations for these systems verify that the proposed symbolic-based method is useful for practitioners and, according to the studied models, has a better performance than the C-C method for the choice of the time delay and embedding dimension. In addition, the method is applied to EEG data in order to study and compare some dynamic characteristics of brain activity under epileptic episodes

【 授权许可】

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