Greedy adaptive decomposition of signals based on nonlinear Fourier atoms
Kit Ian Kou, Hong Li · International Journal of Wavelets Multiresolution and Information Processing · 2016
This paper aims at adaptive decomposition of signals in terms of nonlinear Fourier atoms. Each nonlinear Fourier atom is analytic and mono-component. The algorithm is considered as an adaptive greedy procedure based on nonlinear Fourier atoms. The convergence results for the proposed algorithms show that it is suitable to approximate a signal by a linear combinations of nonlinear Fourier atoms. Experiments are presented to illustrate the proposed algorithm and theory.