2019
DOI: 10.1155/2019/1715673
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Cycle Analysis Method of Tree Ring and Solar Activity Based on Variational Mode Decomposition and Hilbert Transform

Abstract: According to the correlation of tree ring and solar activity, the cycle analysis method based on variational mode decomposition (VMD) and Hilbert transform is proposed. Firstly, the tree ring width of cypress during 1700 to 1955 beside the Huangdi Tomb and the long-term sunspot number during 1700 to 1955, respectively, are decomposed by VMD into a series of intrinsic mode functions (IMFs). Secondly, Hilbert transformation on the decomposed IMF component is performed. Then, the marginal spectra are given and an… Show more

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Cited by 9 publications
(8 citation statements)
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“…Direct analysis of event occurrences is desirable when event data are available. Huang et al (1998) develop the empirical mode decomposition for analyzing nonlinear and nonstationary data (Rilling, Flandrin, and Goncalves (2003); Li et al (2004)). The method decomposes a data set into intrinsic mode functions, which is more flexible than the Fourier transformation.…”
Section: Event Pattern Analysis In the Spatiotemporal Dimensionmentioning
confidence: 99%
“…Direct analysis of event occurrences is desirable when event data are available. Huang et al (1998) develop the empirical mode decomposition for analyzing nonlinear and nonstationary data (Rilling, Flandrin, and Goncalves (2003); Li et al (2004)). The method decomposes a data set into intrinsic mode functions, which is more flexible than the Fourier transformation.…”
Section: Event Pattern Analysis In the Spatiotemporal Dimensionmentioning
confidence: 99%
“… , and are updated alternately, where represents the number of iterations. The specific process is as follows ( Li et al, 2019 ): …”
Section: Basic Theorymentioning
confidence: 99%
“…e MVMD decomposition result of the underwater acoustic signal and the decomposition result of the EMD is shown in Figures 16 and 17. e chaotic component is mainly concentrated in the high-frequency component [36], and the stronger the chaos, the higher the prediction difficulty. To compare the prediction performance of MVMD-OKELM and EMD-OKELM in more detail, this paper selects the high-frequency component imf1 of EMD decomposition and the highfrequency component imf8 of MVMD decomposition for comparison.…”
Section: Underwater Acoustic Signal Prediction Experimentmentioning
confidence: 99%