Empirical mode decomposition (EMD) and Hilbert spectral analysis (HSA) representa desperate attempt to break the suffocating hold on data analysis by the twinassumptions of linearity and stationarity. To analyze the data from nonlinear andnon-stationary processes, various attempts such as Spectrograms, Wavelet analysis,and the Wigner-Ville distribution have been made, but the EMD-HSA approach isunique and different from the existing methods of data analysis. The EMD-HAS istruly an adaptive time-frequency analysis. It does not require an a priori functionalbasis. Instead, the basis functions are derived adaptively from the data by the EMDsifting procedures; the instantaneous frequencies are computed from derivatives ofthe phase functions of the Hilbert transform of the basis functions; the final resultis presented in the time-frequency space. The EMD-HSA is a magnifying glass foranalyzing the data from nonlinear and non-stationary processes. The EMD-HSAresults are intriguing and are no longer shackled by spurious harmonics (the artifactsof imposing a linearity property on a nonlinear system) or limited by theuncertainty principle (the consequence of Fourier transform pairs in data analysis)
Empirical mode decomposition (EMD) and Hilbert spectral analysis (HSA) representa desperate attempt to break the suffocating hold on data analysis by the twinassumptions of linearity and stationarity. To analyze the data from nonlinear andnon-stationary processes, various attempts such as Spectrograms, Wavelet analysis,and the Wigner-Ville distribution have been made, but the EMD-HSA approach isunique and different from the existing methods of data analysis. The EMD-HAS istruly an adaptive time-frequency analysis. It does not require an a priori functionalbasis. Instead, the basis functions are derived adaptively from the data by the EMDsifting procedures; the instantaneous frequencies are computed from derivatives ofthe phase functions of the Hilbert transform of the basis functions; the final resultis presented in the time-frequency space. The EMD-HSA is a magnifying glass foranalyzing the data from nonlinear and non-stationary processes. The EMD-HSAresults are intriguing and are no longer shackled by spurious harmonics (the artifactsof imposing a linearity property on a nonlinear system) or limited by theuncertainty principle (the consequence of Fourier transform pairs in data analysis)