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Blind Separation Combined Frequency Invariant Beamforming and ICA for Far-field Broadband Acoustic Signals.

Authors :
Jun Wang
Xiaofeng Liao
Zhang Yi
Qi Lv
Xianda Zhang
Ying Jia
Source :
Advances in Neural Networks - ISNN 2005 (9783540259138); 2005, p538-543, 6p
Publication Year :
2005

Abstract

Many famous blind source separation (BSS) in frequency domain have been developed while they can still not avoid the permutation problem. We propose a new BSS approach for far-field broadband acoustic signals via combining the frequency invariant bemforming (FIB) technique and complex-valued independent component analysis (ICA). Compared with other frequency methods, our method can avoid the permutation problem and has much faster convergency rate. We also present a new performance measure to evaluate the separation. Finally, the simulation is given to verify the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540259138
Database :
Supplemental Index
Journal :
Advances in Neural Networks - ISNN 2005 (9783540259138)
Publication Type :
Book
Accession number :
32979942
Full Text :
https://doi.org/10.1007/11427445_88