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Flow Empirical Mode Decomposition
2021Decomposing non-stationary signals using Empirical Mode Decomposition (EMD) highly facilitates signal analyses and processing. According to the original algorithm, EMD decomposes the input signal into useful Intrinsic Mode Functions (IMFs). However, EMD has some drawbacks.
Dário Pedro +4 more
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Quadrivariate Empirical Mode Decomposition
The 2010 International Joint Conference on Neural Networks (IJCNN), 2010We introduce a quadrivariate extension of Empirical Mode Decomposition (EMD) algorithm, termed QEMD, as a tool for the time-frequency analysis of nonlinear and non-stationary signals consisting of up to four channels. The local mean estimation of the quadrivariate signal is based on taking real-valued projections of the input in different directions in
Naveed ur Rehman, Danilo P. Mandic
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Improved uniform phase empirical mode decomposition and its application in machinery fault diagnosis
Measurement: Journal of the International Measurement Confederation, 2021Jinde Zheng, Jinyu Tong
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Adaptive Polymorphic Mode Decomposition
Digital Signal ProcessingZhehao Huang, Jinzhao Liu
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Adaptive variational mode decomposition method for signal processing based on mode characteristic
Mechanical Systems and Signal Processing, 2018Zhuo Liu
exaly
A study of the characteristics of white noise using the empirical mode decomposition method
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2004Zhauhua Wu
exaly
THE MULTI-DIMENSIONAL ENSEMBLE EMPIRICAL MODE DECOMPOSITION METHOD
Advances in Adaptive Data Analysis, 2009Zhauhua Wu, Xianyao Chen
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