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Time-frequency approach to underdetermined blind source separation

journal contribution
posted on 2012-02-06, 00:00 authored by S Xie, L Yang, J M Yang, G Zhou, Yong XiangYong Xiang
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.

History

Journal

IEEE transactions on neural networks and learning systems

Volume

23

Issue

2

Pagination

306 - 316

Publisher

IEEE

Location

Piscataway, N. J.

ISSN

2162-237X

eISSN

2162-2388

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2011, IEEE