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Please use this identifier to cite or link to this item: http://hdl.handle.net/10061/8121

Title: Evaluation of Fast-Convergence Algorithm for Blind Source Separation of Real Convolutive Mixture
Authors: Hiroshi Saruwatari
Toshiya Kawamura
Katsuyuki Sawai
Kiyohiro Shikano
Atsunobu Kaminuma
Masao Sakata
Issue Date: Aug-2002
Publisher: IEEE
Start page: 346
End page: 349
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) beamforming based on the estimated DOA; (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 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: ICOSP2002: the 6th International Conference on Signal Processing, August 26-30, 2002.
URI: http://hdl.handle.net/10061/8121
ISBN: 0780374886
Rights: Copyright 2002 IEEE
Text Version: Publisher
Publisher DOI: 10.1109/ICOSP.2002.1181061
Appears in Collections:情報科学研究科 / Graduate School of Information Science

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