English

$L_p$-Sampling recovery for non-compact subclasses of $L_\infty$

Numerical Analysis 2022-10-05 v1 Numerical Analysis Functional Analysis

Abstract

In this paper we study the sampling recovery problem for certain relevant multivariate function classes which are not compactly embedded into LL_\infty. Recent tools relating the sampling numbers to the Kolmogorov widths in the uniform norm are therefore not applicable. In a sense, we continue the research on the small smoothness problem by considering "very" small smoothness in the context of Besov and Triebel-Lizorkin spaces with dominating mixed regularity. There is not much known on the recovery of such functions except of an old result by Oswald in the univariate situation. As a first step we prove the uniform boundedness of the p\ell_p-norm of the Faber-Schauder coefficients in a fixed level. Using this we are able to control the error made by a (Smolyak) truncated Faber-Schauder series in LqL_q with q<q<\infty. It turns out that the main rate of convergence is sharp. As a consequence we obtain results also for S1,1F([0,1]d)S^1_{1,\infty}F([0,1]^d), a space which is ``close'' to the space S11W([0,1]d)S^1_1W([0,1]^d) which is important in numerical analysis, especially numerical integration, but has rather bad Fourier analytic properties.

Keywords

Cite

@article{arxiv.2210.01704,
  title  = {$L_p$-Sampling recovery for non-compact subclasses of $L_\infty$},
  author = {Glenn Byrenheid and Serhii A. Stasyuk and Tino Ullrich},
  journal= {arXiv preprint arXiv:2210.01704},
  year   = {2022}
}
R2 v1 2026-06-28T02:47:14.152Z