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About membership functions estimation

Fuzzy Sets and Systems, 1981
Abstract A logical approach to fuzzy sets method originated by Giles is developed. The infinitely many-valued logic tω is taken as basic. We accept, it is correct to use the strong conjunction by the logical analysis of the summation of fuzzy items. Under some broad conditions it is proved.
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BiCMOS tunable membership function circuits

International Journal of Electronics, 1993
An MOS transconductance amplifier and bipolar current gain cell structure were investigated. The large input voltage range of the MOS transconductance is preserved, while the gain in the bipolar cell is linearly current controlled. These features make the structure suitable for tunable membership function circuits (MFCs) in a fuzzy controller.
ION E. OPRIS, FLORINEL BALTEANU
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Fuzzy membership function optimization

AIP Conference Proceedings, 2012
Goodness of fuzzy control depends on several factors; one of them is shape of membership functions. Assignment of membership functions for clustered data is subjective in nature; however, it cannot be done arbitrarily. A membership function in general form defines only a structure; optimization of its parameters is desirable for good control.
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On elicitation of membership functions

IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 2002
In this study, we elaborate on an important issue of membership function determination. The main point is that any membership estimation procedure should reconcile the semantics of a fuzzy set (regarded as an information granule arising at some level of information abstraction) with the experimental evidence conveyed by numeric data.
W. Pedrycz, G. Vukovich
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Measurement of Membership Functions

1986
Abstract 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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Analytically derived fuzzy membership functions

Cluster Computing, 2017
The numerical algorithms typically used for determining the fuzzy membership functions are iterative, might face convergence issues, and lack in the mathematical theory. This study suggests an analytical approach to the determination of fuzzy membership functions via variational optimization.
Weiping Zhang, Mohit Kumar, Yunfeng Zhou, Jingzhi Yang, Yihua Mao   +4 more
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Tuning of Membership Functions

2001
In 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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Learning membership functions from examples

1993 (2nd) International Symposium on Uncertainty Modeling and Analysis, 2002
Describes the adaptation of a crisp induction algorithm, called constrained generalization, to the building of fuzzy rules. This approach bridges the gap between machine learning and fuzzy logic. An application is learning membership functions from examples, as well as estimating a real-valued attribute.
M. Sebag, M. Schoenauer
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Fuzzy sets and membership functions

Fuzzy Sets and Systems, 1993
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Membership function as an evaluation

Fuzzy Sets and Systems, 1990
This 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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