基于点式准计量的斯科特准计量和斯科特准均匀性

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Chong Shen , Fu-Gui Shi , Xinchao Zhao
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引用次数: 0

摘要

在本文中,我们发展了领域理论中的点准计量空间与斯科特空间之间的一些联系。主要结果包括 (i) 具有 S 形态的斯科特准计量范畴等同于 Shi 意义上的点准量范畴;(ii) 当且仅当拓扑生成的空间 (IX,ωI(T))(其中,ωI(T) 表示从 X 到单位区间 I 的所有下半连续映射族)可以由具有属性 M 的点准度量诱导;③ 提出了斯科特准均匀性的概念,并证明域理论的 d 空间正是斯科特准均匀性空间;④ 建立了斯科特准度量(由第一和第二位作者引入)与斯科特准均匀性之间的关系。具体地说,斯科特准计量正是具有可数基的斯科特准均匀性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scott quasi-metric and Scott quasi-uniformity based on pointwise quasi-metrics

In this paper, we develop some connections between pointwise quasi-metric spaces and Scott spaces in domain theory. The main results include (i) the category of Scott quasi-metrics with S-morphisms is equivalent to that of pointwise quasi-metrics in the sense of Shi; (ii) a topological space (X,T) is quasi-metrizable if and only if the topologically generated space (IX,ωI(T)) (where ωI(T) denotes the family of all lower semi-continuous mappings from X to the unit interval I) can be induced by a pointwise quasi-metric with a property M; (iii) the notion of Scott quasi-uniformity is presented, and it is shown that d-spaces of domain theory are exactly the Scott quasi-uniformizable spaces; (iv) the relationship between Scott quasi-metrics (introduced by the first and second authors) and Scott quasi-uniformities is established. In specific, the Scott quasi-metrics are exactly the Scott quasi-uniformities that has a countable base.

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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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