Sources number estimation and blind separation algorithm based on unsupervised learning
Xie Sheng-li · Systems engineering and electronics · 2009
The two-step approach is often used to separate sources in underdetermined blind separation problem.The first step is to estimate the mixing matrix by clustering algorithms using the observations,in which it is often supposed that the sources number is known,so the two-step approach depends on the prior information about sources number strongly.A novel underdetermined blind separation algorithm based on fuzzy clustering and fuzzy similar matrix is proposed,which can accurately estimate the sources number and the mixing matrix respectively.The last simulations show the good performance of the proposed algorithm.