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Please use this identifier to cite or link to this item: http://hdl.handle.net/10061/8045

Title: Blind Source Separation Based on Fast-Convergence Algorithm Using ICA and Beamforming for Real Convolutive Mixture
Authors: Hiroshi Saruwatari
Toshiya Kawamura
Katsuyuki Sawai
Atsunobu Kamimura
Masao Sakata
Issue Date: May-2002
Publisher: IEEE
Volume: 1
Start page: 921
End page: 924
Abstract: 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 three parts: (1) frequency-domain ICA with direction-of-arrival (DOA) estimation, (2) null beamforming based on the estimated DOA, and (3) integration of (1) and (2) based on the algorithm diversity in both iteration and frequency domain. The inverse of the mixing matrix obtained by ICA is temporally substituted by the matrix based on null beamforming through iterative optimization, and the temporal alternation 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, even under reverberant conditions.
Description: ICASSP2002: IEEE International Conference on Acoustics, Speech and Signal Processing, May 13-17, 2002, Orlando, Florida, US.
URI: http://hdl.handle.net/10061/8045
ISBN: 0780374029
ISSN: 1520-6149
Rights: Copyright 2002 IEEE
Text Version: Publisher
Publisher DOI: 10.1109/ICASSP.2002.5743890
Appears in Collections:情報科学研究科 / Graduate School of Information Science

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