| 长基线时间序列季节项提取和重构方法分析 |
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| 引用本文： | 吉长东,张 萌,沈祎凡.长基线时间序列季节项提取和重构方法分析[J].大地测量与地球动力学,2020,40(8):818-821. |
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| 作者姓名： | 吉长东 张 萌 沈祎凡 |
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| 摘 要： | 运用经验模态分解（EMD）、集合经验模态分解（EEMD）和完备总体经验模态分解（CEEMD）3种方法对原始基线时间序列进行分解，得到各自时间序列的本征函数模态分量（IMF）、相关系数及周期性强度，进而确定其季节项分量，同时通过比较季节项和原始基线时间序列的叠加功率谱图优选分解方法。结果表明，CEEMD方法对基线时间序列季节项提取和重构效果最佳。
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| 关 键 词： | 基线时间序列 季节项 CEEMD 叠加功率谱 |
Analysis of Season Item Extraction and Reconstruction of Long Baseline Time Series |
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| JI Changdong,ZHANG Meng,SHEN Yifan.Analysis of Season Item Extraction and Reconstruction of Long Baseline Time Series[J].Journal of Geodesy and Geodynamics,2020,40(8):818-821. |
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| Authors: | JI Changdong ZHANG Meng SHEN Yifan |
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| Abstract: | In this paper, empirical mode decomposition(EMD), ensemble empirical mode decomposition(EEMD) and complete ensemble empirical mode decomposition(CEEMD) are used to decompose the original baseline time series. The corresponding time series intrinsic mode function(IMF), correlation coefficients and periodic intensity are obtained, and the season components are determined. The decomposition method is optimized by comparing the superposition power spectrum of the season item with the original baseline time series. The results show that CEEMD method has the best effect on extracting and reconstructing season item of baseline time series. |
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| Keywords: | baseline time series season item CEEMD superposition power spectrum |
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