The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
@article{Huang1998TheEM,
title={The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis},
author={N. Huang and Zheng Shen and S. Long and M. Wu and Hsing-Hua Shih and Q. Zheng and N. Yen and C. Tung and H. Liu},
journal={Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences},
year={1998},
volume={454},
pages={903 - 995}
}A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the ‘empirical mode decomposition’ method with which any complicated data set can be decomposed into a finite and often small number of ‘intrinsic mode functions’ that admit well-behaved Hilbert transforms. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to… Expand
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