DocumentCode
890322
Title
On choosing models for linguistic connector words for Mamdani fuzzy logic systems
Author
Wu, Hongwei ; Mendel, Jerry M.
Author_Institution
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
Volume
12
Issue
1
fYear
2004
Firstpage
29
Lastpage
44
Abstract
We examine ten antecedent connector models in the framework of a singleton or nonsingleton fuzzy logic system (FLS), to establish which models can be used. In this work, a usable connector model must lead to a separable firing degree that is a closed-form and piecewise-differentiable function of the membership function parameters and also the parameter characterizing that connector model. Our analysis shows that: for a singleton FLS where the Mamdani-product or Mamdani-minimum implication method is used, all ten antecedent connector models are usable; for a nonsingleton FLS where the Mamdani-product implication method is used, only one antecedent connector model is usable; and for a nonsingleton FLS where the Mamdani-minimum implication method is used, none of the ten antecedent connector models is usable. We also show, by examples, that the parameter of the antecedent connector model provides additional freedom in adjusting a FLS, so that the FLS has the potential to achieve better performance than a FLS that uses the traditional product or minimum t-norm for the antecedent connections.
Keywords
chaos; computational linguistics; fuzzy logic; fuzzy set theory; time series; Mackey-Glass time-series; Mamdani fuzzy logic systems; Mamdani-minimum implication method; Mamdani-product method; antecedent connector models; chaotic time-series; closed-form function; fuzzy set aggregation; linguistic connector words; membership function parameters; piecewise-differentiable function; separable firing degree; singleton firing degrees; soft-ordered weight system; t-conorm; t-norm; Connectors; Fuzzy logic; Fuzzy sets; Fuzzy systems; Image processing; Joining processes; Natural languages; Signal processing; Uncertainty; Upper bound;
fLanguage
English
Journal_Title
Fuzzy Systems, IEEE Transactions on
Publisher
ieee
ISSN
1063-6706
Type
jour
DOI
10.1109/TFUZZ.2003.822675
Filename
1266385
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