Fast-convergence algorithm for ICA-based blind source separation using array signal processing

Author

Saruwatari, Hiroshi ; Kawamura, Toshiya ; Shikano, Kiyohiro

Author_Institution

Graduate Sch. of Inf. Sci., Nara Inst. of Sci. & Technol., Japan

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

464

Lastpage

467

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 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

Keywords

array signal processing; direction-of-arrival estimation; frequency-domain analysis; optimisation; speech processing; BSS; DOA estimation; ICA-based blind source separation; array signal processing; direction-of-arrival estimation; fast-convergence algorithm; fast-convergence optimization; high-convergence optimization; independent component analysis; microphone array system; null beamforrning; Array signal processing; Blind source separation; Direction of arrival estimation; Equations; Frequency domain analysis; Frequency estimation; Independent component analysis; Microphone arrays; Signal processing algorithms; Source separation;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on

Print_ISBN

0-7803-7011-2

Type

conf

DOI

10.1109/SSP.2001.955323

Filename

955323