• DocumentCode
    3388245
  • Title

    Uniqueness of Non-Negative Matrix Factorization

  • Author

    Laurberg, Hans

  • Author_Institution
    Department of of Electronic Systems, Aalborg University, Niels Jernes Vej 12, DK-9220 Aalborg, Denmark, email: hla@es.aau.dk
  • fYear
    2007
  • fDate
    26-29 Aug. 2007
  • Firstpage
    44
  • Lastpage
    48
  • Abstract
    In this paper, two new properties of stochastic vectors are introduced and a strong uniqueness theorem on non-negative matrix factorizations (NMF) is introduced. It is described how the theorem can be applied to two of the common application areas of NMF, namely music analysis and probabilistic latent semantic analysis. Additionally, the theorem can be used for selecting the model order and the sparsity parameter in sparse NMFs.
  • Keywords
    Acoustic noise; Closed-form solution; Feature extraction; Image analysis; Mathematical model; Principal component analysis; Sparse matrices; Spectrogram; Stochastic systems; Text analysis; Non-negative matrix factorization (NMF); model selection; non-negativity; sparse NMF;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing, 2007. SSP '07. IEEE/SP 14th Workshop on
  • Conference_Location
    Madison, WI, USA
  • Print_ISBN
    978-1-4244-1198-6
  • Electronic_ISBN
    978-1-4244-1198-6
  • Type

    conf

  • DOI
    10.1109/SSP.2007.4301215
  • Filename
    4301215
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3388245