Sparse Component Analysis for Underdetermined Blind Source Separation
LI Chang-li · Journal of Guangdong Ocean University · 2009
The main method,namely,sparse component analysis(SCA),which is used to solve underdetermined BSS,is analyzed.This class of methods consists of two stages: first clustering and then optimization,all of which firstly estimate the mixing matrix and then estimate the source signals given the estimated mixing matrix by means of optimization.Various algorithms for clustering and optimization in underdetermined BSS are summarized,and the close relationship between underdetermined BSS,SCA and compressed sensing is discussed.Finally prospect for underdetermined BSS is made.