Empirical Mode Decomposition and some operators to estimate Instantaneous Frequency: A comparative study

The aim of the present work is to illustrate how the empirical mode decomposition (EMD) can be associated with demodulation methods to estimate the instantaneous frequency (IF) of multicomponent non stationary signals. The IF estimation of three methods, namely, Hilbert-Huang transform (HHT) [10], EMD-DESA (Discrete Energy Separation Algorithm)also known as Teager-Huang transform (THT) [2] [5], and B-spline version of the EMD-DESA called EMD-ESA-BS [1] are compared on AM-FM signal corrupted with an additive white Gaussian noise of varying signal to noise ratio (SNR). The obtained results show that for very low SNR the EMD-ESA-BS with regularization performs better than the HHT, the THT and the EMD-ESA- BS without regularization. For high SNR values all the methods globally have the same behavior, but the EMD-ESA-BS without regularization gives the best estimation.