# Method for Mode Mixing Separation in Empirical Mode Decomposition

@article{Fosso2017MethodFM, title={Method for Mode Mixing Separation in Empirical Mode Decomposition}, author={Olav Bjarte Fosso and Marta Molinas}, journal={arXiv: Methodology}, year={2017} }

The Empirical Mode Decomposition (EMD) is a signal analysis method that separates multi-component signals into single oscillatory modes called intrinsic mode functions (IMFs), each of which can generally be associated to a physical meaning of the process from which the signal is obtained. When the phenomena of mode mixing occur, as a result of the EMD sifting process, the IMFs can lose their physical meaning hindering the interpretation of the results of the analysis. In the paper, "One or Two…

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## 12 Citations

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A method to separate spectral components that reside within the same octave, is presented based on reversing the conditions by which mode mixing occurs, which has potential application for identifying the cause of different oscillatory modes with spectral proximity present in the smart grid.

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An analytical framework is developed that isolates oscillatory signals from time-series using masked Empirical Mode Decomposition to quantify dynamical changes in the shape of individual cycles (along with amplitude, frequency and phase) using instantaneous frequency and finds that the instantaneous frequency tracks non-sinusoidal shapes in both simulated and real data.

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This thesis delves into the two fields of signal analysis and small-signal stability of power systems, using Prony’s method, Robust Recursive Least Squares (RRLS) and the FFT based Welch's method, as well as the EMD and Clustering technique.

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