• DocumentCode
    1056706
  • Title

    Measuring fuzzy uncertainty

  • Author

    Pal, Nikhil R. ; Bezdek, James C.

  • Author_Institution
    Machine Intelligence Unit, Indian Stat. Inst., Calcutta, India
  • Volume
    2
  • Issue
    2
  • fYear
    1994
  • fDate
    5/1/1994 12:00:00 AM
  • Firstpage
    107
  • Lastpage
    118
  • Abstract
    First, this paper reviews several well known measures of fuzziness for discrete fuzzy sets. Then new multiplicative and additive classes are defined. We show that each class satisfies five well-known axioms for fuzziness measures, and demonstrate that several existing measures are relatives of these classes. The multiplicative class is based on nonnegative, monotone increasing concave functions. The additive class requires only nonnegative concave functions. Some relationships between several existing and the new measures are established, and some new properties are derived. The relative merits and drawbacks of different measures for applications are discussed. A weighted fuzzy entropy which is flexible enough to incorporate subjectiveness in the measure of fuzziness is also introduced. Finally, we comment on the construction of measures that may assess all of the uncertainties associated with a physical system
  • Keywords
    fuzzy set theory; additive classes; discrete fuzzy sets; fuzziness measures; fuzzy uncertainty measures; multiplicative class; nonnegative monotone increasing concave functions; weighted fuzzy entropy; Additives; Digital images; Entropy; Face detection; Fuzzy sets; Fuzzy systems; Image analysis; Machine vision; Measurement uncertainty; Probability distribution;
  • fLanguage
    English
  • Journal_Title
    Fuzzy Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6706
  • Type

    jour

  • DOI
    10.1109/91.277960
  • Filename
    277960