• DocumentCode
    1385530
  • Title

    A property of the minimum vectors of a regularizing functional defined by means of the absolute norm

  • Author

    Alliney, Stefano

  • Author_Institution
    Dipt. di Matematica, Bologna Univ., Italy
  • Volume
    45
  • Issue
    4
  • fYear
    1997
  • fDate
    4/1/1997 12:00:00 AM
  • Firstpage
    913
  • Lastpage
    917
  • Abstract
    We consider a regularizing functional defined by means of the l 1 norm, where the regularization is obtained using first differences; as is well-known, such a functional can be put in relation with recursive median filters of appropriate window length. We show that at least one of the minima is reached at a vector, whose components have values over the same discrete set of the given signal. This suggests a simple method to refine the approximate solution to the regularization problem, which can be obtained with recursive median filters of increasing order. We also report an example of application, where the refinement method is employed for a signal detection problem
  • Keywords
    approximation theory; filtering theory; functional analysis; median filters; recursive filters; signal detection; absolute norm; approximate solution; l1 norm; minimum vectors; recursive median filters; refinement method; regularization problem; regularizing functional; signal detection; window length; Bayesian methods; Convolution; Filters; Mathematics; Maximum likelihood estimation; Parameter estimation; Signal detection; Signal processing; Signal processing algorithms; Vectors;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.564179
  • Filename
    564179