Type-2 fuzzy logic systems

  • Authors:

  • N. N. Karnik;J. M. Mendel;Qilian Liang

  • Affiliations:

  • Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA;-;-

  • Venue:
  • IEEE Transactions on Fuzzy Systems
  • Year:
  • 1999

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Abstract

We introduce a type-2 fuzzy logic system (FLS), which can handle rule uncertainties. The implementation of this type-2 FLS involves the operations of fuzzification, inference, and output processing. We focus on “output processing,” which consists of type reduction and defuzzification. Type-reduction methods are extended versions of type-1 defuzzification methods. Type reduction captures more information about rule uncertainties than does the defuzzified value (a crisp number), however, it is computationally intensive, except for interval type-2 fuzzy sets for which we provide a simple type-reduction computation procedure. We also apply a type-2 FLS to time-varying channel equalization and demonstrate that it provides better performance than a type-1 FLS and nearest neighbor classifier