Sparse Blind Source Deconvolution with Application to High Resolution Frequency Analysis

  • Tryphon T. Georgiou
  • Allen Tannenbaum


The title of the paper refers to an extension of the classical blind source separation where the mixing of unknown sources is assumed in the form of convolution with impulse response of unknown linear dynamics. A further key assumption of our approach is that source signals are considered to be sparse with respect to a known dictionary, which suggests a mixed L 1/L 2-optimization as a possible formalism for solving the un-mixing problem. We demonstrate the effectiveness of the framework numerically.


Impulse Response Sparse Representation Blind Source Separation Toeplitz Matrice Gradient Projection Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Berlin Heidelberg 2010

Authors and Affiliations

  • Tryphon T. Georgiou
    • 1
  • Allen Tannenbaum
    • 2
    • 3
  1. 1.University of MinnesotaMinneapolisUSA
  2. 2.Georgia Institute of TechnologyAtlantaUSA
  3. 3.Technion, Israel Institute of TechnologyHaifaIsrael

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