Underdetermined blind source separation by parallel factor analysis in time-frequency domain

Yang, Liu, Lv, Jun and Xiang, Yong 2013, Underdetermined blind source separation by parallel factor analysis in time-frequency domain, Cognitive computation, vol. 5, pp. 207-214, doi: 10.1007/s12559-012-9177-9.

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Title Underdetermined blind source separation by parallel factor analysis in time-frequency domain
Author(s) Yang, Liu
Lv, Jun
Xiang, YongORCID iD for Xiang, Yong orcid.org/0000-0003-3545-7863
Journal name Cognitive computation
Volume number 5
Start page 207
End page 214
Total pages 8
Publisher Springer New York LLC
Place of publication New York, N. Y.
Publication date 2013-06
ISSN 1866-9956
Keyword(s) parallel factor analysis
underdetermined blind source separation
Wigner-Ville distribution
Summary This paper presents a new time-frequency approach to the underdetermined blind source separation using the parallel factor decomposition of third-order tensors. Without any constraint on the number of active sources at an auto-term time-frequency point, this approach can directly separate the sources as long as the uniqueness condition of parallel factor decomposition is satisfied. Compared with the existing two-stage methods where the mixing matrix should be estimated at first and then used to recover the sources, our approach yields better source separation performance in the presence of noise. Moreover, the mixing matrix can be estimated at the same time of the source separation process. Numerical simulations are presented to show the superior performance of the proposed approach to some of the existing two-stage blind source separation methods that use the time-frequency representation as well.
Language eng
DOI 10.1007/s12559-012-9177-9
Field of Research 090609 Signal Processing
Socio Economic Objective 890104 Mobile Telephone Networks and Services
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2012, Springer Science+Business Media, LLC
Persistent URL http://hdl.handle.net/10536/DRO/DU:30047782

Document type: Journal Article
Collection: School of Information Technology
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