• Title/Summary/Keyword: fuzzy norm

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FIXED POINT THEOREMS IN FUZZY METRIC SPACES FOR MAPPINGS WITH SOME CONTRACTIVE TYPE CONDITIONS

  • Patir, Bijoy;Goswami, Nilakshi;Mishra, Lakshmi Narayan
    • Korean Journal of Mathematics
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    • v.26 no.2
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    • pp.307-326
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    • 2018
  • In this paper, we derive some fixed point theorems in fuzzy metric spaces for self mappings satisfying different contractive type conditions. Some of these theorems generalize some results of Wairojjana et al. (Fixed Point Theory and Applications (2015) 2015:69). Several examples in support of the theorems are also presented here.

FIXED POINT THEOREM ON SOME ORDERED METRIC SPACES AND ITS APPLICATION

  • CHANG HYEOB SHIN
    • Journal of applied mathematics & informatics
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    • v.42 no.1
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    • pp.93-104
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    • 2024
  • In this paper, we will prove a fixed point theorem for self-mappings on a generalized quasi-ordered metric space which is a generalization of the concept of a generalized metric space with a partial order and we investigate a genralized quasi-ordered metric space related with fuzzy normed spaces. Further, we prove the stability of some functional equations in fuzzy normed spaces as an application of our fixed point theorem.

A Fixed Point for Pair of Maps in Intuitionistic Fuzzy Mtric Space

  • Park, Jong-Seo;Kim, Seon-Yu
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.3
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    • pp.159-164
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    • 2007
  • Park, Park and Kwun[6] is defined the intuitionistic fuzzy metric space in which it is a little revised from Park[5]. According to this paper, Park, Kwun and Park[11] Park and Kwun[10], Park, Park and Kwun[7] are established some fixed point theorems in the intuitionistic fuzzy metric space. Furthermore, Park, Park and Kwun[6] obtained common fixed point theorem in the intuitionistic fuzzy metric space, and also, Park, Park and Kwun[8] proved common fixed points of maps on intuitionistic fuzzy metric spaces. We prove a fixed point for pair of maps with another method from Park, Park and Kwun[7] in intuitionistic fuzzy metric space defined by Park, Park and Kwun[6]. Our research are an extension of Vijayaraju and Marudai's result[14] and generalization of Park, Park and Kwun[7], Park and Kwun[10].

ON A FUZZY BANACH SPACE

  • Rhie, G.S.;Hwang, I.A.
    • Journal of the Chungcheong Mathematical Society
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    • v.13 no.1
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    • pp.71-78
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    • 2000
  • The main goal of this paper is to prove the following theorem ; Let (X, ${\rho}_1$) be a fuzzy normed linear space over K and (Y, ${\rho}_2$) be a fuzzy Banach space over K. If ${\chi}_{B_{{\parallel}{\cdot}{\parallel}}}{\supseteq}{\rho}*$, then (CF(X,Y), ${\rho}*$) is a fuzzy Banach space, where ${\rho}*(f)={\vee}{\lbrace}{\theta}{\wedge}\frac{1}{t({\theta},f)}\;{\mid}\;{\theta}{\in}(0,1){\rbrace}$, $f{\in}CF(X,Y)$, $B_{{\parallel}{\cdot}{\parallel}}$ is the closed unit ball on (CF(X, Y), ${\parallel}{\cdot}{\parallel}$ and ${\parallel}f{\parallel}={\vee}{\lbrace}P^2_{{\alpha}^-}(f(x))\;{\mid}\;P^1_{{\alpha}^-}(x)=1,\;x{\in}X{\rbrace}$, $f{\in}CF(X,Y)$, ${\alpha}{\in}(0,1)$.

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H∞ Control of T-S Fuzzy Systems Using a Fuzzy Basis- Function-Dependent Lyapunov Function (퍼지 기저함수에 종속적인 Lyapunov 함수를 이용한 T-S 퍼지 시스템의 H∞ 제어)

  • Choi, Hyoun-Chul;Chwa, Dong-Kyoung;Hong, Suk-Kyo
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.7
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    • pp.615-623
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    • 2008
  • This paper proposes an $H_{\infty}$ controller design method for Takagi-Sugeno (T-S) fuzzy systems using a fuzzy basis-function-dependent Lyapunov function. Sufficient conditions for the guaranteed $H_{\infty}$ performance of the T-S fuzzy control system are given in terms of linear matrix inequalities (LMIs). These LMI conditions are further used for a convex optimization problem in which the $H_{\infty}-norm$ of the closed-loop system is to be minimized. To facilitate the basis-function-dependent Lyapunov function approach and thus improve the closed-loop system performance, additional decision variables are introduced in the optimization problem, which provide an additional degree-of-freedom and thus can enlarge the solution space of the problem. Numerical examples show the effectiveness of the proposed method.

COMMON FIXED POINT THEOREMS IN INTUITIONISTIC FUZZY METRIC SPACES

  • Turkoglu D.;Alaca C.;Cho Y.J.;Yildiz C.
    • Journal of applied mathematics & informatics
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    • v.22 no.1_2
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    • pp.411-424
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    • 2006
  • The purpose of this paper, using the idea of intuitionistic fuzzy set due to Atanassov [2], we define the notion of intuitionistic fuzzy metric spaces (see, [1]) due to Kramosil and Michalek [17] and Jungck's common fixed point theorem ([11]) is generalized to intuitionistic fuzzy metric spaces. Further, we first formulate the definition of weakly commuting and R-weakly commuting mappings in intuitionistic fuzzy metric spaces and prove the intuitionistic fuzzy version of Pant's theorem ([21]).

FIXED POINT THEOREMS IN FUZZY METRIC SPACES, FUZZY 2-METRIC SPACES AND FUZZY 3-METRIC SPACES USING SEMI-COMPATIBILITY

  • Singh, Bijendra;Jain, Shishir;Jain, Shobha
    • East Asian mathematical journal
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    • v.23 no.2
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    • pp.175-195
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    • 2007
  • The object of this paper is to introduce the notion of semi-compatible maps in fuzzy metric spaces, fuzzy 2-metric spaces and fuzzy 3-metric spaces and to establish three common fixed point theorems for these spaces for four self-maps. These results improve, extend and generalize the results of [16]. As an application, these results have been used to obtain translation and generalization of Grabeic's contraction principle in the new settings. All the result presented in this paper are new.

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Image Denoising via Fast and Fuzzy Non-local Means Algorithm

  • Lv, Junrui;Luo, Xuegang
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1108-1118
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    • 2019
  • Non-local means (NLM) algorithm is an effective and successful denoising method, but it is computationally heavy. To deal with this obstacle, we propose a novel NLM algorithm with fuzzy metric (FM-NLM) for image denoising in this paper. A new feature metric of visual features with fuzzy metric is utilized to measure the similarity between image pixels in the presence of Gaussian noise. Similarity measures of luminance and structure information are calculated using a fuzzy metric. A smooth kernel is constructed with the proposed fuzzy metric instead of the Gaussian weighted L2 norm kernel. The fuzzy metric and smooth kernel computationally simplify the NLM algorithm and avoid the filter parameters. Meanwhile, the proposed FM-NLM using visual structure preferably preserves the original undistorted image structures. The performance of the improved method is visually and quantitatively comparable with or better than that of the current state-of-the-art NLM-based denoising algorithms.

A note on a triangular norm hierarchy

  • Hong, Dug-Hun
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.139-145
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    • 2002
  • In Cretu (2001), triangular norms and their hierarchy are investigated. In this paper, we give new proofs which are significantly shorter than those given in Cretu, applying a known result which involves only one argument of one-place rather than two-place argument s by Klement et al.(1997).

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