Difference and Wavelet Characterizations of Distances from Functions in Lipschitz Spaces to Their Subspaces
Feng Dai, Eero Saksman, Dachun Yang, Wen Yuan, Yangyang Zhang

TL;DR
This paper provides wavelet and difference-based characterizations of the distance from Lipschitz functions to their subspaces, linking geometric approximation measures to function space properties.
Contribution
It introduces a novel framework connecting Lipschitz space distances with wavelet and difference characterizations, extending to various advanced function spaces.
Findings
Characterizes distances in Lipschitz spaces via wavelet and difference methods.
Establishes equivalence between epsilon quantities and approximation distances.
Extends results to Sobolev, Besov, and Triebel–Lizorkin spaces.
Abstract
Let denote the Lipschitz space of order on , which consists of all such that, for some constant and some integer , \begin{equation*} \label{0-1}\Delta_r f(x,y): =\sup_{|h|\leq y} |\Delta_h^r f(x)|\leq L y^s, \ x\in\mathbb{R}^n, \ y \in(0, 1]. \end{equation*} Here (and throughout the article) refers to continuous functions, and is the usual -th order difference operator with step . For each and , let , and let be a suitably defined nonnegative extended real-valued function on the Borel -algebra of subsets of . Let…
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Taxonomy
TopicsAdvanced Banach Space Theory · Functional Equations Stability Results · Mathematical Analysis and Transform Methods
