Independent Component Analysis and Signal Separation

Volume 5441 of the series Lecture Notes in Computer Science pp 106-113

Minimum Determinant Constraint for Non-negative Matrix Factorization

  • Reinhard SchachtnerAffiliated withCIMLG / Biophysics, University of RegensburgInfineon Technologies AG
  • , Gerhard PöppelAffiliated withInfineon Technologies AG
  • , Ana Maria ToméAffiliated withDETI / IEETA, Universidade de Aveiro
  • , Elmar W. LangAffiliated withCIMLG / Biophysics, University of Regensburg

* Final gross prices may vary according to local VAT.

Get Access


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.