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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.
Published in:
Neural Networks and Learning Systems, IEEE Transactions on
(Volume:23
,
Issue:
2
)
Date of Publication: Feb. 2012
- Page(s):
- 306 - 316
- ISSN :
- 2162-237X
- INSPEC Accession Number:
- 12509375
- Digital Object Identifier :
- 10.1109/TNNLS.2011.2177475
- Product Type:
- Journals & Magazines
- Date of Publication :
- 06 January 2012
- Date of Current Version :
- 06 February 2012
- Issue Date :
- Feb. 2012
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