L 粗空间的规范性

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Yi Shi , Hui Yang
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引用次数: 0

摘要

对于完全分布网格 L,我们引入了一个 L 粗空间的概念,它可以被视为概率均匀空间的大规模类似物。本文的主要目标是研究能诱导 L 值粗临近空间的 L-粗空间的性质。首先,我们引入了一个 L 值粗邻域系统的概念,并证明了由此产生的类别与 L 值粗邻域空间的类别同构。然后,我们研究了粗连接 L-粗空间和渐近连接 L 值渐近相似空间的正态性,并证明这两个正态性是重合的。更重要的是,我们证明了当且仅当一个粗连接的 L-coarse 空间是粗正态的时候,它才会诱导出一个 L 值粗近似空间。最后,我们指出前面的结果对于渐近连接的 L 值渐近相似空间也是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The normality of L-coarse spaces

For L being a completely distributive lattice, we introduce a notion of L-coarse spaces, which can be regarded as a large-scale analogue of probabilistic uniform spaces. The main goal of this paper is to investigate the properties of L-coarse spaces that can induce L-valued coarse proximity spaces. First of all, we introduce a notion of L-valued coarse neighborhood systems, and show that the resulting category is isomorphic to that of L-valued coarse proximity spaces. Then we study the normality of coarsely connected L-coarse spaces and of asymptotically connected L-valued asymptotic resemblance spaces, and show that these two normality properties are coincident. More importantly, we show that a coarsely connected L-coarse space induces an L-valued coarse proximity if and only if it is coarsely normal. We conclude with noting that the previous result are also valid for asymptotically connected L-valued asymptotic resemblance spaces.

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来源期刊
Fuzzy Sets and Systems
Fuzzy Sets and Systems 数学-计算机:理论方法
CiteScore
6.50
自引率
17.90%
发文量
321
审稿时长
6.1 months
期刊介绍: Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.
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