A wavelet-based mode decomposition

We propose a wavelet-based method for analyzing non-stationary data. The idea, inspired by the empirical mode decomposition, is to decompose a data set into a finite number of components, well separated in the time-frequency plane, plus a residue, such that each component has a zero mean and is associated to one frequency only. When applied to climatic data, this method gives interesting results.