Method for eliminating mode mixing of empirical mode decomposition based on the revised blind source separation

Authors:
Baoping Tang;Shaojiang Dong;Tao Song
Affiliations:
The State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400030, People's Republic of China;The State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400030, People's Republic of China;The State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400030, People's Republic of China
Venue:
Signal Processing
Year:
2012

Citing 6
Cited 1

Practical method for determining the minimum embedding dimension of a scalar time series

Physica D
Independent component analysis: algorithms and applications

Neural Networks
Optimal soft morphological filter for periodic noise removal using a particle swarm optimiser with passive congregation

Signal Processing
An alternative envelope approach for empirical mode decomposition

Digital Signal Processing
The study of the intermittency test filtering character of Hilbert-Huang transform

Mathematics and Computers in Simulation
Handbook of Blind Source Separation: Independent Component Analysis and Applications

Handbook of Blind Source Separation: Independent Component Analysis and Applications

Partly ensemble empirical mode decomposition: An improved noise-assisted method for eliminating mode mixing

Signal Processing

Quantified Score

Hi-index	0.08

Visualization

Abstract

Since mode mixing of empirical mode decomposition (EMD) is mainly caused by the intermittence and noise, we propose a novel method to eliminate mode mixing of EMD based on the revised blind source separation. To this aim, an optimal morphological filter is employed to eliminate the noise. As a result, the component of mode mixing caused by noise is suppressed. Furthermore, the de-noised signal is decomposed into different intrinsic mode function (IMF) components through the EMD algorithm. Since it is impossible to apply blind source separation to a single channel signal directly, the IMF component, which has mode mixing is chosen and reconstructed in the phase space. Following that, the equivalent hypothetical signals are obtained. Finally, an improved fixed-point algorithm based on independent component analysis (ICA) is introduced to separate the overlapping components. The analysis of simulation and practical application demonstrates that our proposed method can effectively tackle the mode mixing problem of EMD.