DocumentCode :
20604
Title :
Simplified Interval Type-2 Fuzzy Logic Systems
Author :
Mendel, Jerry M. ; Xinwang Liu
Author_Institution :
Ming Hsieh Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
Volume :
21
Issue :
6
fYear :
2013
fDate :
Dec. 2013
Firstpage :
1056
Lastpage :
1069
Abstract :
Type reduction (TR) followed by defuzzification is commonly used in interval type-2 fuzzy logic systems (IT2 FLSs). Because of the iterative nature of TR, it may be a computational bottleneck for the real-time applications of an IT2 FLS. This has led to many direct approaches to defuzzification that bypass TR, the simplest of which is the Nie-Tan direct defuzzification method (NT method). This paper provides some theoretical analyses of the NT method that answer the question “Why is the NT method good to use?” This paper also provides a direct relationship between TR followed by defuzzification (using KM algorithms) and the NT method. It also provides an improved NT method. Numerical examples illustrate our theoretical results and suggest that the NT method is a very good way to simplify an interval type-2 fuzzy set.
Keywords :
approximation theory; fuzzy set theory; IT2 FLS; KM algorithms; Karnik-Mendel algorithms; NT method; Nie-Tan direct defuzzification method; TR; interval type-2 fuzzy set; simplified interval type-2 fuzzy logic systems; type reduction; Algorithm design and analysis; Approximation methods; Computer architecture; Frequency selective surfaces; Fuzzy logic; Real-time systems; Uncertainty; Defuzzification; Karnik–Mendel (KM) algorithms; Nie–Tan (NT) method; interval type-2 fuzzy set (IT2 FS); type reduction (TR);
fLanguage :
English
Journal_Title :
Fuzzy Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6706
Type :
jour
DOI :
10.1109/TFUZZ.2013.2241771
Filename :
6416036
Link To Document :
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