• DocumentCode
    1206549
  • Title

    Enhanced Karnik--Mendel Algorithms

  • Author

    Wu, Dongrui ; Mendel, Jerry M.

  • Author_Institution
    Ming Hsieh Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
  • Volume
    17
  • Issue
    4
  • fYear
    2009
  • Firstpage
    923
  • Lastpage
    934
  • Abstract
    The Karnik-Mendel (KM) algorithms are iterative procedures widely used in fuzzy logic theory. They are known to converge monotonically and superexponentially fast; however, several (usually two to six) iterations are still needed before convergence occurs. Methods to reduce their computational cost are proposed in this paper. Extensive simulations show that, on average, the enhanced KM algorithms can save about two iterations, which corresponds to more than a 39% reduction in computation time. An additional (at least) 23% computational cost can be saved if no sorting of the inputs is needed.
  • Keywords
    computational complexity; fuzzy logic; iterative methods; computational cost; enhanced Karnik-Mendel algorithms; fuzzy logic theory; iterative procedures; Enhanced Karnik--Mendel (EKM) algorithms; Enhanced Karnik-Mendel algorithms; Karnik--Mendel (KM) algorithms; Karnik-Mendel algorithms; interval type-2 fuzzy sets; interval type-2 fuzzy sets (IT2FSs); novel weighted averages; type-reduction; uncertainty measures;
  • fLanguage
    English
  • Journal_Title
    Fuzzy Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6706
  • Type

    jour

  • DOI
    10.1109/TFUZZ.2008.924329
  • Filename
    4505357