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Canonical decomposition approach for underdetermined blind separation of non-disjoint sources
Received date: 2014-09-22
Revised date: 2014-11-19
Online published: 2014-11-24
Supported by
Fundamental Research Funds for the Central Universities (K5051302018)
This paper proposes a method of underdetermined blind separation of non-disjoint sources (UBSS) based on fourth-order cumulant (FO) and tensor decomposition. By semi-invariance of high-order cumulant, the FO is presented as statistics of the observed signal as fourth-order tensor; hence the mixed matrix is estimated by tensor decomposition with line search alternating least square. Finally, with the estimated matrix, sources are recovered by minimum mean-squared error-based beamforming. Simulations illustrate the validity of the method and show that the proposed method outperforms the existing methods in performance significantly.
AI Xiaofan, LUO Yongjiang, ZHAO Guoqing. Canonical decomposition approach for underdetermined blind separation of non-disjoint sources[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(10): 3393-3400. DOI: 10.7527/S1000-6893.2014.0319
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