• DocumentCode
    322054
  • Title

    Structured total least squares with fixed elements

  • Author

    Lemos, Rodrigo Pinto ; Lopes, Amauri

  • Author_Institution
    Sch. of Electr. Eng, Fed. Univ. of Goias, Brazil
  • Volume
    2
  • fYear
    1997
  • fDate
    3-6 Aug 1997
  • Firstpage
    841
  • Abstract
    In this paper, we propose the association of the structured total least squares method to the unstructured total least squares method with some elements of the augmented data matrix kept fixed during the optimization process. This association yields a structured total least squares method with fixed elements. This method allows us to treat problems with a great deal of structure, such as sparse problems, as well as to keep exact data intact during the optimization
  • Keywords
    least squares approximations; optimisation; sparse matrices; augmented data matrix; fixed elements; optimization process; sparse problems; structured total least squares; Computational efficiency; Ear; Least squares approximation; Least squares methods; Matrix decomposition; Maximum likelihood estimation; Multidimensional systems; Optimization methods; Signal resolution; Sparse matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1997. Proceedings of the 40th Midwest Symposium on
  • Conference_Location
    Sacramento, CA
  • Print_ISBN
    0-7803-3694-1
  • Type

    conf

  • DOI
    10.1109/MWSCAS.1997.662205
  • Filename
    662205