Convergent bivariate subdivision scheme with nonnegative mask whose support is non-convex

IF 2.6 2区数学 Q1 MATHEMATICS, APPLIED

Applied and Computational Harmonic Analysis Pub Date : 2024-02-01 DOI:10.1016/j.acha.2024.101636

Li Cheng

引用次数: 0

Abstract

Recently we have characterized the convergence of bivariate subdivision scheme with nonnegative mask whose support is convex by means of the so-called connectivity of a square matrix, which is derived by a given mask. The convergence in this case can be checked in linear time with respected to the size of a square matrix. This paper will focus on the characterization of such schemes with non-convex supports.

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支持非凸的非负掩码收敛双变量细分方案

最近，我们通过由给定掩码导出的所谓正方形矩阵的连通性，确定了具有非负掩码的双变量细分方案的收敛性。这种情况下的收敛性可以在尊重方阵大小的线性时间内检验。本文将重点讨论这种具有非凸支持的方案的特征。

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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来源期刊

Applied and Computational Harmonic Analysis 物理-物理：数学物理

CiteScore

5.40

自引率

4.00%

发文量

审稿时长

22.9 weeks

期刊介绍： Applied and Computational Harmonic Analysis (ACHA) is an interdisciplinary journal that publishes high-quality papers in all areas of mathematical sciences related to the applied and computational aspects of harmonic analysis, with special emphasis on innovative theoretical development, methods, and algorithms, for information processing, manipulation, understanding, and so forth. The objectives of the journal are to chronicle the important publications in the rapidly growing field of data representation and analysis, to stimulate research in relevant interdisciplinary areas, and to provide a common link among mathematical, physical, and life scientists, as well as engineers.