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Building a hierarchical representation of membership functions
Proceedings Tenth IEEE International Conference on Tools with Artificial Intelligence (Cat. No.98CH36294), 2002Deriving inference rules from training examples is one of the most common machine-learning approaches. Fuzzy systems that can automatically derive fuzzy if-then rules and membership functions from numeric data have recently been developed. In this paper, we propose a new hierarchical representation for membership functions, and design a procedure to ...
Tzung-Pei Hong, Jyh-Bin Chen
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Choosing membership functions of linguistic terms
The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03., 2004The shapes of terms used in fuzzy systems have adopted several 'conventions'. Terms are almost invariably normalised (having a maximum membership value of 1), convex (having a single maximum or plateau maxima) and distinct (being restricted in their degree of overlap: often expressed as some variation on the concept that all membership values at any ...
Garibaldi, J. M., John, Robert, 1955-
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On fuzzy ellipsoid numbers and membership functions
Journal of Intelligent & Fuzzy Systems, 2016In this paper, the operations of fuzzy ellipsoid numbers and the direct relationship between the joint membership function and the edge membership functions are investigated. First, we prove that the general scalar multiplication (defined by Zadeh’s expansion) of fuzzy ellipsoid numbers preserves the closeness of the operation, but the general addition
Guixiang Wang +3 more
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Membership function as an evaluation
Fuzzy Sets and Systems, 1990This paper is devoted to the membership functions of fuzzy sets. First, the author presents different kinds of mathematical forms of the membership functions. Next, he extracts the different demands and determines the rational class of membership functions. Finally, he shows the connections between evaluation operators and membership functions.
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A CMOS PWL fuzzy membership function
Proceedings of ISCAS'95 - International Symposium on Circuits and Systems, 2002The membership function, classically constructed from piecewise linear (PWL) functions, is one of the most important components in fuzzy neural systems. Here we give an improved current mode CMOS circuit suitable for design of fuzzy membership PWL functions.
S. Ahmadi +2 more
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The Membership Function and Its Measurement
2013Perhaps the most fundamental concept in fuzzy set theory is the membership function [24, 25]. Fuzzy sets allow for gradual degrees of membership and the membership function is a measure of that degree. The meaning of the membership function has been a question for everyone including Zadeh himself who advocated a linguistic approach [26–28] from the ...
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Membership functions in automatic harmonization system
Proceedings. 1998 28th IEEE International Symposium on Multiple- Valued Logic (Cat. No.98CB36138), 2002We propose fuzzy reasoning to put harmony to melody in automatic harmonization system. We have been considering the following fuzzy sets and membership functions in the system. The system has two fuzzy sets of "conformability between melody and tonality" as the degree of fitness /spl mu//sub A/(y/sub n/) and "conformability between tonality and ...
Masataka Tokumaru +3 more
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On Obfuscating Set-Membership Predicate Functions
2013 5th International Conference on Intelligent Networking and Collaborative Systems, 2013Obfuscation was first studied in computer programming field, which could be explained as a compiler that translates computer codes into an unintelligible form while preserving the original functionality. Since obfuscation for cryptographic purposes was raised out, several positive results have been presented in despite of the general impossibility ...
Rong Cheng, Feng Diao, Fangguo Zhang
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Tuning of Membership Functions
2001In the previous chapter, we discuss extraction of the three types of fuzzy rules: those with pyramidal membership functions, those with polyhedral regions, and those with ellipsoidal regions using the data included in the associated clusters. Since these fuzzy rules are generated without considering the overlap between classes, their classification ...
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Measurement of Membership Functions
1986Abstract Empirical measurement of membership functions of fuzzy sets are considered with the fundamental axioms of measurement theory. An experimental construction of fuzzy set membership leads to a realization of stochastic fuzziness and a type II fuzzy set representation. Axioms of measurement can be validated with a probabilistic interpretation.
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