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

journal contribution
posted on 2013-06-01, 00:00 authored by L Yang, J Lv, Yong XiangYong Xiang
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.

History

Journal

Cognitive computation

Volume

5

Pagination

207 - 214

Publisher

Springer New York LLC

Location

New York, N. Y.

ISSN

1866-9956

eISSN

1866-9964

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2012, Springer Science+Business Media, LLC