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Nonlinear Analysis of Magnetospheric Data Part II. Dynamical Characteristics of the Ae Index Time Series and Comparison with Nonlinear Surrogate Data : Volume 6, Issue 2 (30/11/-0001)

By Pavlos, G. P.

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Book Id: WPLBN0004019944
Format Type: PDF Article :
File Size: Pages 20
Reproduction Date: 2015

Title: Nonlinear Analysis of Magnetospheric Data Part II. Dynamical Characteristics of the Ae Index Time Series and Comparison with Nonlinear Surrogate Data : Volume 6, Issue 2 (30/11/-0001)  
Author: Pavlos, G. P.
Volume: Vol. 6, Issue 2
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
-0001
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Kugiumtzis, D., Sarris, E. T., Hatzigeorgiu, N., Athanasiu, M. A., Diamantidis, D., & Pavlos, G. P. (-0001). Nonlinear Analysis of Magnetospheric Data Part II. Dynamical Characteristics of the Ae Index Time Series and Comparison with Nonlinear Surrogate Data : Volume 6, Issue 2 (30/11/-0001). Retrieved from http://hawaiilibrary.net/


Description
Description: Department of Electrical and Computer Engineering, Demokritos University of Thrace, 67100 Xanthi, Greece. In this study we have used dynamical characteristies such as Lyapunov exponents, nonlinear dynamic models and mutual information for the nonlinear analysis of the magnetospheric AE index time series. Similarly with the geometrical characteristic studied in Pavlos et al. (1999b), we have found significant differences between the original time series and its surrogate data. These results also suggest the rejection of the null hypothesis that the AE index belongs to the family of stochastic linear signals undergoing a static nonlinear distortion. Finally, we believe that these results support the hypothesis of nonlinearity and chaos for the magnetospheric dynamics.

Summary
Nonlinear analysis of magnetospheric data Part II. Dynamical characteristics of the AE index time series and comparison with nonlinear surrogate data

 

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