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Successive Variational Mode Decomposition (SVMD.m)

version 1.1.1 (739 KB) by Mojtaba Nazari
This code is the corrected version of the SVMD (Ver. 1.1.1) which is a powerful signal decomposition algorithm.

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Updated 01 Sep 2021

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The SVMD is a robust method that extracts the modes successively and does not need to know the number of modes (unlike VMD). The method considers the mode as a signal with a maximally compact spectrum, as VMD does. It has been demonstrated that the SVMD method without knowing the number of modes converges to the same modes as VMD does with knowing the precise number of modes. Moreover, the computational complexity of SVMD is much lower than that of VMD. Also, another advantage of SVMD over VMD is more robustness against the initial values of the center frequencies of modes.

Cite As

Mojtaba Nazari (2021). Successive Variational Mode Decomposition (SVMD.m) (https://www.mathworks.com/matlabcentral/fileexchange/98649-successive-variational-mode-decomposition-svmd-m), MATLAB Central File Exchange. Retrieved .

Nazari, Mojtaba, and Sayed Mahmoud Sakhaei. “Successive Variational Mode Decomposition.” Signal Processing, vol. 174, Elsevier BV, Sept. 2020, p. 107610, doi:10.1016/j.sigpro.2020.107610.

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Nazari, Mojtaba, and Sayed Mahmoud Sakhaei. “Variational Mode Extraction: A New Efficient Method to Derive Respiratory Signals from ECG.” IEEE Journal of Biomedical and Health Informatics, vol. 22, no. 4, Institute of Electrical and Electronics Engineers (IEEE), July 2018, pp. 1059–67, doi:10.1109/jbhi.2017.2734074.

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Dragomiretskiy, Konstantin, and Dominique Zosso. “Variational Mode Decomposition.” IEEE Transactions on Signal Processing, vol. 62, no. 3, Institute of Electrical and Electronics Engineers (IEEE), Feb. 2014, pp. 531–44, doi:10.1109/tsp.2013.2288675.

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MATLAB Release Compatibility
Created with R2021a
Compatible with any release
Platform Compatibility
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