对收敛群范畴的新认识

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Lingqiang Li, Qiu Jin
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引用次数: 0

摘要

⊤-Ȥ收敛群是格值拓扑群的自然扩展,是一种新引入的数学结构。本文将进一步探讨Ȥ收敛群的理论。主要结果包括(1) 通过Ȥ滤波的⊙积,它拥有一个新颖的表征,而且它是可局部化的,即每个Ȥ收敛群都是由底层群的标识元处的收敛唯一决定的。(2)它的子类--拓扑Ȥ收敛群的定义可以通过去掉拓扑条件(TT)来简化。(3) 它具有均匀性,即每个Ȥ收敛群都可以从一个Ȥ均匀收敛空间重构出来。(4)函数空间上存在自然群结构和Ȥ收敛结构,这使得它成为一个Ȥ收敛群。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fresh look at the category of ⊤-convergence groups
⊤-convergence groups is a natural extension of lattice-valued topological groups, which is a newly introduced mathematical structure. In this paper, we will further explore the theory of ⊤-convergence groups. The main results include: (1) It possesses a novel characterization through the ⊙-product of ⊤-filters, and it is localizable, meaning that each ⊤-convergence group is uniquely determined by the convergence at the identity element of the underlying group. (2) The definition of its subcategory, the topological ⊤-convergence groups, can be simplified by removing the topological condition (TT). (3) It exhibits uniformization, which means that each ⊤-convergence group can be reconstructed from a ⊤-uniformly convergent space. (4) There exists a natural group structure and ⊤-convergence structure on the function space, which makes it a ⊤-convergence group.
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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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