• DocumentCode
    155611
  • Title

    Bound constrained weighted NMF for industrial source apportionment

  • Author

    Limem, A. ; Puigt, M. ; Delmaire, G. ; Roussel, G. ; Courcot, D.

  • Author_Institution
    LISIC, Univ. Lille Nord de France, Calais, France
  • fYear
    2014
  • fDate
    21-24 Sept. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In our recent work, we introduced a constrained weighted Non-negative Matrix Factorization (NMF) method using a β-divergence cost function. We assumed that some components of the factorization were known and were used to inform our NMF algorithm. In this paper, we are provided some intervals of possible values for some factorization components. We thus introduce an extended version of our previous work combining an improved divergence expression and some matrix normalizationswhile using the known / bounded information. Some experiments on simulated mixtures of particulate matter sources show the relevance of these approaches.
  • Keywords
    blind source separation; matrix decomposition; β-divergence cost function; bound constrained weighted NMF; factorization components; industrial source apportionment; matrix normalizations; nonnegative matrix factorization; particulate matter sources; Chemicals; Indexes; Linear matrix inequalities; Noise measurement; Signal to noise ratio; Sparse matrices; Vectors; Beta divergence; Blind source separation; Non-negative matrix factorization; Normalization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning for Signal Processing (MLSP), 2014 IEEE International Workshop on
  • Conference_Location
    Reims
  • Type

    conf

  • DOI
    10.1109/MLSP.2014.6958851
  • Filename
    6958851