posted on 2019-06-12, 09:32authored bySimon Hubbert, Jeremy Levesley
In this paper we give a short note showing convergence rates for periodic approximation of smooth functions by multilevel Gaussian convolution. We will use the Gaussian scaling in the convolution at the finest level as a proxy for degrees of freedom d in the model. We will show that, for functions in the native space of the Gaussian, convergence is of the order (Formula Presented.). This paper provides a baseline for what should be expected in discrete convolution, which will be the subject of a follow up paper.
History
Citation
Lecture Notes in Computational Science and Engineering, 2019, 126, pp. 83-92 Numerical Mathematics and Advanced Applications ENUMATH 2017.
Author affiliation
/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Mathematics
Source
Numerical Mathematics and Advanced Applications ENUMATH 2017.
Version
AM (Accepted Manuscript)
Published in
Lecture Notes in Computational Science and Engineering
The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.