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Time-frequency approach to underdetermined blind source separation
journal contributionposted 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.
JournalIEEE transactions on neural networks and learning systems
Pagination306 - 316
LocationPiscataway, N. J.
Publication classificationC1 Refereed article in a scholarly journal
Copyright notice2011, IEEE
Khatri-Rao productunderdetermined blind source separationWigner-Ville distributionScience & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer Science, Hardware & ArchitectureComputer Science, Theory & MethodsEngineering, Electrical & ElectronicComputer ScienceEngineeringIDENTIFICATIONMIXTURESALGORITHMS