Lp-Sampling recovery for non-compact subclasses of L∞

IF 1.3 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Frontiers in Applied Mathematics and Statistics Pub Date : 2023-08-24 DOI:10.3389/fams.2023.1216331
G. Byrenheid, S. Stasyuk, T. Ullrich
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Abstract

In this article, we study the sampling recovery problem for certain relevant multivariate function classes on the cube [0, 1]d, which are not compactly embedded into L∞([0,1]d). Recent tools relating the sampling widths to the Kolmogorov or best m-term trigonometric widths in the uniform norm are therefore not applicable. In a sense, we continue the research on the small smoothness problem by considering limiting smoothness in the context of Besov and Triebel-Lizorkin spaces with dominating mixed regularity such that the sampling recovery problem is still relevant. There is not much information available on the recovery of such functions except for a previous result by Oswald in the univariate case and Dinh Dũng in the multivariate case. As a first step, we prove the uniform boundedness of the ℓp-norm of the Faber coefficients at a fixed level by Fourier analytic means. Using this, we can control the error made by a (Smolyak) truncated Faber series in Lq([0,1]d) with q <∞. It turns out that the main rate of convergence is sharp. Thus, we obtain results also for S1,∞1F([0,1]d), a space “close” to S11W([0,1]d), which is important in numerical analysis, especially numerical integration, but has rather poor Fourier analytical properties.
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L∞非紧子类的lp采样恢复
本文研究了非紧嵌在L∞([0,1]d)上的多维函数类[0,1]d上的采样恢复问题。因此,将采样宽度与统一范数中的Kolmogorov或最佳m项三角宽度相关的最新工具不适用。从某种意义上说,我们继续研究小平滑问题,考虑Besov和triiebel - lizorkin空间中占主导地位的混合正则性的限制平滑性,使得采样恢复问题仍然相关。除了Oswald在单变量情况下的先前结果和Dinh Dũng在多变量情况下的结果外,没有太多关于这些函数恢复的信息。作为第一步,我们用傅里叶解析方法证明了Faber系数的p-范数在固定水平上的一致有界性。利用这种方法,我们可以控制(Smolyak)截断的Faber级数在q <∞的Lq([0,1]d)上产生的误差。事实证明,主要的收敛速度非常快。因此,我们也得到了S1,∞1F([0,1]d)的结果,这是一个“接近”S11W([0,1]d)的空间,它在数值分析,特别是数值积分中很重要,但具有相当差的傅里叶解析性质。
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来源期刊
Frontiers in Applied Mathematics and Statistics
Frontiers in Applied Mathematics and Statistics Mathematics-Statistics and Probability
CiteScore
1.90
自引率
7.10%
发文量
117
审稿时长
14 weeks
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