• DocumentCode
    37541
  • Title

    Invexity of the Minimum Error Entropy Criterion

  • Author

    Syed, M. ; Pardalos, Panos ; Principe, Jose

  • Author_Institution
    Dept. of Ind. & Syst. Eng., Univ. of Florida, Gainesville, FL, USA
  • Volume
    20
  • Issue
    12
  • fYear
    2013
  • fDate
    Dec. 2013
  • Firstpage
    1159
  • Lastpage
    1162
  • Abstract
    In this letter, optimization properties of Minimization of Error Entropy (MEE) and Minimization of Error Entropy with Fiducial points (MEEF) are presented. It is proved that by varying the kernel parameter of the MEE and/or MEEF objective function, the resulting problem, in general leads to an invex problem. Furthermore, for certain values of the kernel parameter it is shown that the problems may transform to convex or pseudo-convex problems.
  • Keywords
    convex programming; entropy; minimisation; MEEF; invex problem; kernel parameter; minimization of error entropy with fiducial points; minimum error entropy criterion invexity; optimization properties; pseudo convex problems; Entropy; Kernel; Measurement uncertainty; Minimization; Optimization; Robustness; Signal processing algorithms; Entropic learning; error entropy; information potential; information theoretic learning;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2013.2283425
  • Filename
    6619422
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=37541