离散概率量值数据的细分方案

IF 2.9 2区数学 Q1 MATHEMATICS, APPLIED

Applied Mathematics Letters Pub Date : 2024-07-22 DOI:10.1016/j.aml.2024.109233

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引用次数: 0

摘要

本文论述了一种新的细分方案对离散概率量值数据的逼近。它的构造依赖于线性细分和最优传输之间的耦合。本文通过数学分析来研究其收敛性。最后描述了两个测试案例，以强调其能力：第一个案例与点云插值有关，第二个案例则是在图像近似框架下的首次尝试。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Subdivision scheme for discrete probability measure-valued data

This paper deals with the approximation of discrete probability measure-valued data by a new subdivision scheme. Its construction relies on a coupling between linear subdivision and optimal transport. A mathematical analysis is performed to study its convergence. Two test cases are finally described to emphasize its capability: the first one is related to point cloud interpolation while the second one is a first attempt in the framework of image approximation.

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来源期刊

Applied Mathematics Letters 数学-应用数学

CiteScore

7.70

自引率

5.40%

发文量

347

审稿时长

10 days

期刊介绍： The purpose of Applied Mathematics Letters is to provide a means of rapid publication for important but brief applied mathematical papers. The brief descriptions of any work involving a novel application or utilization of mathematics, or a development in the methodology of applied mathematics is a potential contribution for this journal. This journal''s focus is on applied mathematics topics based on differential equations and linear algebra. Priority will be given to submissions that are likely to appeal to a wide audience.