Minimum Determinant Constraint for Non-negative Matrix Factorization

  • Reinhard Schachtner
  • Gerhard Pöppel
  • Ana Maria Tomé
  • Elmar W. Lang
Conference paper

DOI: 10.1007/978-3-642-00599-2_14

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5441)
Cite this paper as:
Schachtner R., Pöppel G., Tomé A.M., Lang E.W. (2009) Minimum Determinant Constraint for Non-negative Matrix Factorization. In: Adali T., Jutten C., Romano J.M.T., Barros A.K. (eds) Independent Component Analysis and Signal Separation. ICA 2009. Lecture Notes in Computer Science, vol 5441. Springer, Berlin, Heidelberg

Abstract

We propose a determinant criterion to constrain the solutions of non-negative matrix factorization problems and achieve unique and optimal solutions in a general setting, provided an exact solution exists. We demonstrate with illustrative examples how optimal solutions are obtained using our new algorithm detNMF and discuss the difference to NMF algorithms imposing sparsity constraints.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Reinhard Schachtner
    • 1
    • 2
  • Gerhard Pöppel
    • 2
  • Ana Maria Tomé
    • 3
  • Elmar W. Lang
    • 1
  1. 1.CIMLG / BiophysicsUniversity of RegensburgRegensburgGermany
  2. 2.Infineon Technologies AGRegensburgGermany
  3. 3.DETI / IEETAUniversidade de AveiroAveiroPortugal

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