Blind Determination of the Number of Sources Using Distance Correlation

Amir Weiss*, Arie Yeredor

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


A novel blind estimate of the number of sources from noisy, linear mixtures is proposed in this letter. Based on Székely et al.'s distance correlation measure, we define the sources' dependence criterion (SDC), from which our estimate arises. Unlike most previously proposed estimates, the SDC estimate exploits the full independence of the sources and noise, as well as the non-Gaussianity of the sources (as opposed to the Gaussianity of the noise), via implicit use of high-order statistics. This leads to a more robust, resilient, and stable estimate w.r.t. the mixing matrix and the noise covariance structure. Empirical simulation results demonstrate these virtues on top of superior performance in comparison with current state-of-the-art estimates.

Original languageEnglish
Article number8653964
Pages (from-to)828-832
Number of pages5
JournalIEEE Signal Processing Letters
Issue number6
StatePublished - Jun 2019


  • Distance correlation
  • high-order statistics
  • independent component analysis
  • number of sources


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