On the difference between empirical mode decomposition and wavelet decomposition in the nonlinear time series

The method of empirical mode decomposition (EMD) based Hilbert transformation is that separate the nonlinear time series into intrinsic mode functions (IMFs) with different time scale by using EMD, then apply the Hilbert transformation to every IMF to get the Hilbert spectrum. By systematically comparing the advantages and disadvantages between EMD and wavelet decomposition (WD), between Hilbert transformation and wavelet transformation in transacting nonlinear time series using ideal time series and O-18 time series of Guliya ice core on the Tibetan Plateau, we present some improving measures to reduce the disadvantages. The result of investigation show that the combination of EMD-based and WD-based methods may be more effectively in recognizing the main information of the time series.