Source recovery of underdetermined blind source separation based on SCMP algorithm

摘要

In this study, a new algorithm subspace complementary matching pursuit (SCMP) is developed for source recovery of underdetermined blind source separation. The proposed SCMP is more simplified than the conventional complementary matching pursuit (CMP) algorithm. SCMP algorithm selects more than one atom in each iteration to reduce computational complexity, and replaces the norm minimisation involved in CMP with the approximate norm minimisation to ensure higher recovery accuracy. Numerical results show that, compared with the existing algorithms for source recovery, such as CMP, orthogonal CMP (OCMP), optimised OCMP and sparsity adaptive CMP, the proposed SCMP algorithm significantly reduces the computational time with improved recovery accuracy.