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CLC number: TN911

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

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Journal of Zhejiang University SCIENCE A 2007 Vol.8 No.8 P.1271-1276

http://doi.org/10.1631/jzus.2007.A1271


A novel blind deconvolution algorithm using single frequency bin


Author(s):  ZHANG Gui-bao, LI Jia-wen, LI Cong-xin

Affiliation(s):  National Die & Mold CAD Engineering Research Center, Shanghai Jiao Tong University, Shanghai 200030, China

Corresponding email(s):   gbzhangf2@sjtu.edu.cn

Key Words:  Blind deconvolution, Single frequency bin, Convolutive mixture


ZHANG Gui-bao, LI Jia-wen, LI Cong-xin. A novel blind deconvolution algorithm using single frequency bin[J]. Journal of Zhejiang University Science A, 2007, 8(8): 1271-1276.

@article{title="A novel blind deconvolution algorithm using single frequency bin",
author="ZHANG Gui-bao, LI Jia-wen, LI Cong-xin",
journal="Journal of Zhejiang University Science A",
volume="8",
number="8",
pages="1271-1276",
year="2007",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2007.A1271"
}

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%T A novel blind deconvolution algorithm using single frequency bin
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%A LI Jia-wen
%A LI Cong-xin
%J Journal of Zhejiang University SCIENCE A
%V 8
%N 8
%P 1271-1276
%@ 1673-565X
%D 2007
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2007.A1271

TY - JOUR
T1 - A novel blind deconvolution algorithm using single frequency bin
A1 - ZHANG Gui-bao
A1 - LI Jia-wen
A1 - LI Cong-xin
J0 - Journal of Zhejiang University Science A
VL - 8
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SP - 1271
EP - 1276
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Y1 - 2007
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2007.A1271


Abstract: 
Former frequency-domain blind devolution algorithms need to consider a large number of frequency bins and recover the sources in different orders and with different amplitudes in each frequency bin, so they suffer from permutation and amplitude indeterminacy troubles. Based on sliding discrete Fourier transform, the presented deconvolution algorithm can directly recover time-domain sources from frequency-domain convolutive model using single frequency bin. It only needs to execute blind separation of instantaneous mixture once there are no permutation and amplitude indeterminacy troubles. Compared with former algorithms, the algorithm greatly reduces the computation cost as only one frequency bin is considered. Its good and robust performance is demonstrated by simulations when the signal-to-noise-ratio is high.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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[8] Smaragdis, P., 1998. Blind separation of convolved mixtures in the frequency domain. Neurocomputing, 22:21-34.

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