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Type-2 fuzzy logic systems

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3 Author(s)
N. N. Karnik ; Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA ; J. M. Mendel ; Qilian Liang

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

Published in:

IEEE Transactions on Fuzzy Systems  (Volume:7 ,  Issue: 6 )