Fast-Convergence Algorithm for ICA-Based Blind Source Separation Utilizing Array Signal Processing

HSC2001: IEEE International Workshop on Hands-Free Speech Communication, April 9-11, 2001, Kyoto, Japan.We propose a new algorithm for blind source separation (BSS), in which independent component analysis (ICA) and beamforming are combined to resolve the low-convergence problem through optimization in ICA. The proposed method consists of the folIowing two parts: frequency-domain ICA with direction-of-arrival (DOA) estimation, and null beamforming based on the estimated DOA. The alternation of learning between ICA and beamforming can realize fast- and high-convergence optimization. The results of the signal separation experiments reveal that the signal separation performance of the proposed algorithm is superior to that of the conventional ICA-based BSS method