Blind Source Separation via a Weak Exclusion Principle

In this paper, we propose a generalized Blind Source Separation (BSS) method using a novel assumption which we call “weak exclusion” principle. We first give the mathematical definition of the exclusion criterion and propose an iterative algorithm to minimize it. We then test WEP in simulated and real datasets, compared with other four methods. The experiments on synthetic and real datasets demonstrate that WEP outperforms the other methods, both in terms of accuracy and in terms of speed.