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 orcid.org/0000-0003-3545-7863 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 Collections: Faculty of Science, Engineering and Built Environment School of Information Technology 2018 ERA Submission Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Mon, 13 Aug 2012, 12:58:50 EST Mon, 29 Oct 2012, 15:04:49 EST Mon, 29 Oct 2012, 15:07:20 EST Fri, 13 Jun 2014, 14:44:22 EST Tue, 03 Feb 2015, 13:11:06 EST Filtered Full Citation counts:   Cited 90 times in TR Web of Science Cited 114 times in Scopus Search Google Scholar Access Statistics: 723 Abstract Views, 7 File Downloads  -  Detailed Statistics Created: Mon, 13 Aug 2012, 12:58:50 EST