Empirical Mode Decomposition

First published: 2014

Brief summary

PyEMD documentation for empirical mode decomposition.

Article

Empirical Mode Decomposition is covered by the linked source. PyEMD documentation for empirical mode decomposition.

The material from PyEMD describes a method for detecting, decomposing, testing or reproducing structure in time-series data.

Reliable use requires attention to sampling, trend, missing values, noise, boundaries, parameter choices and multiple testing. Sensitivity checks help assess stability.

No method can confirm a genuine cycle from an attractive graph or isolated peak alone. Significance requires an appropriate null model and documented preprocessing.

Source details and credits

• Source / publisher: PyEMD
• Source type: Software docs
• URL type: WWW
• Credits: PyEMD
• URL: https://pyemd.readthedocs.io/en/latest/