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Proceedings Paper

Ensemble empirical mode decomposition applied to long-term solar time series analysis
Author(s): Jianmei An; Yunfang Cai; Yi Qi; Xianping Wang; Yongyan Zuo
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Paper Abstract

Solar time series manifests nonlinear and non-stationary behaviors, and perhaps multi-modal dynamical processes operating in solar magnetic indicators. In the present work, the novel ensemble empirical mode decomposition (EEMD) is applied to study the monthly distribution of sunspot areas produced by the extended time series of solar activity indices (ESAI) database in the time interval from 1821 January to 1989 December. It is established that the quasi-periodic variations of monthly sunspot areas consist of at least three well-defined dynamical components: one is the short-term variations which are obviously smaller than one year, the second one is the mid-term variations with periodic scales varying from 1 year to 15 years, and the last component is the periodic variation with periodicities larger than 15 years. The analysis results indicate the EEMD technique is an advanced tool for analyzing the weakly nonlinear and non-stationary dynamical behaviors of solar magnetic activity cycle.

Paper Details

Date Published: 26 July 2018
PDF: 5 pages
Proc. SPIE 10828, Third International Workshop on Pattern Recognition, 1082819 (26 July 2018); doi: 10.1117/12.2502101
Show Author Affiliations
Jianmei An, Chongqing Univ. of Arts and Sciences (China)
Yunfang Cai, Yunnan Observatories (China)
Yi Qi, Chongqing Univ. of Arts and Sciences (China)
Xianping Wang, Chongqing Univ. of Arts and Sciences (China)
Yongyan Zuo, Chongqing Univ. of Arts and Sciences (China)

Published in SPIE Proceedings Vol. 10828:
Third International Workshop on Pattern Recognition
Xudong Jiang; Zhenxiang Chen; Guojian Chen, Editor(s)

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