Robust Local Mean Decomposition (RLMD)
The RLMD is an improved local mean decomposition powered by a set of optimization strategies. The optimization strategies can deal with boundary condition, envelope estimation, and sifting stopping criterion in the LMD. It simultaneously extracts a set of mono-component signals (called product functions) and their associated demodulation signals (i.e. AM signal and FM signal) from a mixed signal, which is the most attracting feature comparing with other adaptive signal processing methods, such as the EMD. The RLMD can be used for time-frequency analysis.
References:
[1] Zhiliang Liu, Yaqiang Jin, Ming J. Zuo, and Zhipeng Feng. Time-frequency representation based on robust local mean decomposition for multi-component AM-FM signal analysis. Mechanical Systems and Signal Processing. 95: 468-487, 2017.
[2] Smith J S. The local mean decomposition and its application to EEG perception data[J]. Journal of the Royal Society Interface, 2005, 2(5): 443-454.
[3] G. Rilling, P. Flandrin and P. Goncalves. On empirical mode decomposition and its algorithms. IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing NSIP-03, Grado (I), June 2003
Cita come
Zhiliang Liu, Yaqiang Jin, Ming J. Zuo, and Zhipeng Feng. Time-frequency representation based on robust local mean decomposition for multi-component AM-FM signal analysis. Mechanical Systems and Signal Processing. 95: 468-487, 2017.
Liu Zhiliang (2024). Robust Local Mean Decomposition (RLMD) (https://www.mathworks.com/matlabcentral/fileexchange/66935-robust-local-mean-decomposition-rlmd), MATLAB Central File Exchange. Recuperato .
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