• Journal of applied mathematics & informatics
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• v.5 no.1
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• pp.153-162
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• 1998

We study limits of sums of fuzzy numbers with different spreads and different shape functions where addition is defined by the sup-t-norm. We show the existence of the limit of the series of fuzzy numbers and prove the uniform continuity of the limit. Finally we investigate a law of large numbers for sequences of fuzzy numbers.

• Communications of the Korean Mathematical Society
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• v.27 no.2
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• pp.265-277
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• 2012

In this paper we establish two common fixed point theorems in fuzzy metric spaces. These theorems are generalisations of the Banach contraction mapping principle and the Kannan's fixed point theorem respectively in fuzzy metric spaces. Our result is also supported by examples.

• Communications of the Korean Mathematical Society
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• v.24 no.4
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• pp.565-579
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• 2009

In this paper, we give some new fixed point theorems for contractive type mappings in intuitionistic fuzzy metric spaces. We improve and generalize the well-known fixed point theorems of Banach [4] and Edelstein [8] in intuitionistic fuzzy metric spaces. Our main results are intuitionistic fuzzy version of Fang's results [10]. Further, we obtain some applications to validate our main results to product spaces.

• Journal of applied mathematics & informatics
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• v.41 no.3
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• pp.541-552
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• 2023

In 2005, Patterson studied lacunary statistical convergence of double sequences of real numbers and, in 2009, Mursaleen introduced notion of lacunary statistical convergence of single sequences in intuitionistic fuzzy normed space. The current work intends to investigate the lacunary statistical convergence of double sequences and some significant conclusions on the algebra of the lacunary statistical limit of double sequences in intuitionistic fuzzy normed space. In addition, we have studied some examples to support the definitions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.9-15
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• 1998

In this paper, we introduce new results of law large numbers for mutually T-related fuzzy numbers, when T is Archimedean t-norm and spreads are random variables, and generalize earlier result of Fullr[FSS 45(1992) 299-303].

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.457-465
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• 2004

Ramik[7] introduced a fuzzy goal programming (FGP)problem that generalizes a standard goal programming (GP) problem with fuzzy alternatives, fuzzy objective functions and fuzzy deviation functions for measuring the deviation between attained and desired goals being fuzzy. However, it is known that this FGP tends to produce an approximate solution since it uses an approximate fuzzy multiplication operation to solve the resultant fuzzy model. In this paper, we show that this FGP sometimes leads to the wrong decision. We also propose a procedure that gets the exact solution to overcome these problems. The method is based on $T_M$ (min norm)-based fuzzy operations using $\alpha-cut$ representations. We consider the same example as used in Ramik and investigate how our procedures are compared to Ramik's.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1053-1056
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• 2004

In this article we have applied Schweizer & Sklars t-norm based similarity measures to classification task. We will compare results to fuzzy similarity measure based classification and show that sometimes better results can be found by using these measures than fuzzy similarity measure. We will also show that classification results are not so sensitive to p values with Schweizer & Sklars measures than when fuzzy similarity is used. This is quite important when one does not have luxury of tuning these kind of parameters but needs good classification results fast.

• Communications of the Korean Mathematical Society
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• v.21 no.1
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• pp.89-100
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• 2006

In this paper we prove a common fixed point theorem for compatible maps of type $(\beta)$ on fuzzy metric spaces with arbitrary continuous t-norm.

• Journal of Industrial Technology
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• v.13
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• pp.33-41
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• 1993

In this paper, a new LMS algorithm with a fuzzy variable step size (FVS LMS) is presented. The change of step size ${\mu}$, at each iteration which is increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. As a measure of the misadaptation degree, the norm of the cross correlation between the estimation error and input signal is used. Simulation results are presented to compare the performance of the FVSS LMS algorithm with the normalized LMS algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.1
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• pp.30-35
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• 2009

We investigate the properties of fuzzy relations, metrics and $\bigodot$-equivalence relation on a stsc quantale lattice L and a commutative cqm-lattice. In particular, pseudo-(quasi-) metrics induce $\bigodot$-(quasi)-equivalence relations.