On the approximation of functions with line singularities by ridgelets

JOURNAL OF APPROXIMATION THEORY

卷:237

Article

Obermeier, Axel¹  Grohs, Philipp^1,2 

[1] Swiss Fed Inst Technol, Seminar Appl Math, Ramistr 101, CH-8092 Zurich, Switzerland

[2] Univ Vienna, Fak Math, Oskar Morgenstern Pl 1, A-1090 Vienna, Austria

关键词: Ridgelets;    Nonlinear approximation;    Advection equations;   

DOI  :  10.1016/j.jat.2018.05.003

来源: Elsevier

【 摘 要 】

In Grohs and Obermeier (2015), the authors discussed the existence of numerically feasible solvers for advection equations that run in optimal computational complexity. In this paper, we complete the last remaining requirement to achieve this goal - by showing that ridgelets, on which the solver is based, approximate functions with line singularities (which may appear as solutions to the advection equation) with the best possible approximation rate (up to arbitrarily small 1 > 0) if the functions decay sufficiently fast, and with a slight penalty if not. Structurally, the proof resembles Candes (2001), where a similar result was proved for a different ridgelet construction, which is however not well-suited for use in a PDE solver (and in particular, not suitable for the CDD-schemes (Cohen et al., 2001) we are interested in). Due to the differences between the two ridgelet constructions, we have to deal with quite a different set of issues, but are also able to relax the (support) conditions on the function being approximated. Finally, the proof employs a new convolution-type estimate that could be of independent interest due to its sharpness. (C) 2018 Elsevier Inc. All rights reserved.

【 授权许可】

Free