Time-frequency approach to underdetermined blind source separation

Xie, Shengli, Yang, Liu, Yang, Jun-Mei, Zhou, Guoxu and Xiang, Yong 2012, Time-frequency approach to underdetermined blind source separation, IEEE transactions on neural networks and learning systems, vol. 23, no. 2, pp. 306-316.

Attached Files
Name Description MIMEType Size Downloads

Title Time-frequency approach to underdetermined blind source separation
Author(s) Xie, Shengli
Yang, Liu
Yang, Jun-Mei
Zhou, Guoxu
Xiang, Yong
Journal name IEEE transactions on neural networks and learning systems
Volume number 23
Issue number 2
Start page 306
End page 316
Total pages 11
Publisher IEEE
Place of publication Piscataway, N. J.
Publication date 2012-02-06
ISSN 2162-237X
2162-2388
Keyword(s) Khatri-Rao product
underdetermined blind source separation
Wigner-Ville distribution
Summary This paper presents a new time-frequency (TF) underdetermined blind source separation approach based on Wigner-Ville distribution (WVD) and Khatri-Rao product to separate N non-stationary sources from M(M <; N) mixtures. First, an improved method is proposed for estimating the mixing matrix, where the negative value of the auto WVD of the sources is fully considered. Then after extracting all the auto-term TF points, the auto WVD value of the sources at every auto-term TF point can be found out exactly with the proposed approach no matter how many active sources there are as long as N ≤ 2M-1. Further discussion about the extraction of auto-term TF points is made and finally the numerical simulation results are presented to show the superiority of the proposed algorithm by comparing it with the existing ones.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2011, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30047001

Document type: Journal Article
Collection: School of Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 9 times in TR Web of Science
Google Scholar Search Google Scholar
Access Statistics: 58 Abstract Views, 4 File Downloads  -  Detailed Statistics
Created: Mon, 13 Aug 2012, 12:58:50 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.