摘要：The sparsity of signals in their transformed domain is widely used for under-determined blind source separation. The most challenging task of under-determined BSS is to estimate the mixing matrix. In this paper, a new cost function is proposed to detect the sparsest sub-band. Samples in the sub-band can be used to estimate the mixing matrix. Finally some numerical experiments are performed to evaluate the effectiveness of the proposed algorithm.
