A method of underdetermined blind source separation in time-domain

摘要

In this article, we consider the problem of sources separation from their underdetermined instantaneous mixtures via time-domain. First, we introduced an algorithm based on differential kurtosis to separate non-stationary sources one by one under underdetermined case. Then, the rest sources are recovered using an algorithm based on second-order statistics. The simulation results show that the proposed method can separate sources of super- and sub-Gaussian distributions, and it has superior performance compared to other conventional methods.