EMD和小波方法在太阳黑子数据中的应用

2009 International Conference on Environmental Science and Information Application Technology Pub Date : 2011-03-26 DOI:10.1109/ICIST.2011.5765337

Yong Wang, Yuanyuan Ding, Qingzhou Luo, Qilong Miao

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引用次数: 1

摘要

太阳黑子是气候变化的主要原因之一。对太阳黑子周期的研究有助于研究气候变化。基于该方法，利用时间序列分析技术、经验模态分解(EMD)和小波分析，揭示了太阳黑子数据在不同时间尺度上的变化特征。与小波变换相比，EMD可以分析非平稳和非线性时间序列数据，准确地揭示时间序列在时频域上的主要特征。

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Application of EMD and wavelet method to sunspot data

The sunspot is one of the main cause of climate change. Research on the sunspot cycle is conducive to study climate change. Based on new approach, using time series analysis technique, empirical mode decomposition (EMD) and wavelet, to reveal the detail features of the variability of sunspot data on various time scales. In comparison with wavelet transform, EMD can analyze non-stationary and non-linear time series data and reveal the main characteristics of time series on time-frequency domains precisely.

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2009 International Conference on Environmental Science and Information Application Technology

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