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

Hiroshi Saruwatari, Toshiya Kawamura, and Kiyohiro Shikano

To appear at Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA01), Mohonk Mountain Resort, NY, 21-24 October 2001


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 following 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.

Server START Conference Manager
Update Time 5 Jul 2001 at 16:08:04
Start Conference Manager
Conference Systems