Sampling with derivatives in finitely generated shift-invariant spaces

IF 2.1 2区数学 Q1 MATHEMATICS, APPLIED

Journal of Computational and Applied Mathematics Pub Date : 2025-04-17 DOI:10.1016/j.cam.2025.116692

Kumari Priyanka, A. Antony Selvan

引用次数: 0

Abstract

The problem of sampling with derivatives involves reconstructing functions from their derivative sample values on a suitable sequence of points via sampling expansions. In this paper, we explore the sampling and interpolation problem that deals with derivative samples in finitely generated shift-invariant spaces. We characterize the complete interpolation of periodic nonuniform samples involving derivatives. We provide a sufficient condition for a nonuniform sampling set to reconstruct functions in finitely generated shift-invariant spaces.

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有限生成平移不变空间中的导数抽样

带导数的抽样问题涉及到通过抽样展开式在合适的点序列上从其导数样本值重构函数。本文研究了有限生成平移不变空间中导数样本的采样和插值问题。我们刻画了包含导数的周期非均匀样本的完全插值。给出了非均匀采样集在有限生成的移不变空间中重构函数的一个充分条件。

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

Journal of Computational and Applied Mathematics 数学-应用数学

CiteScore

5.40

自引率

4.20%

发文量

437

审稿时长

3.0 months

期刊介绍： The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.