Spline Approximation on Sparse Grids

Scott Kersey, Chukwugozirim Ehirim

Research output: Contribution to book or proceedingConference articlepeer-review

Abstract

We present a compact sparse grid operator to multivariate functions on [0,1]d using the combination technique and tensor product spline interpolation. The construction is based on univariate spline interpolation using full end knots supported on [0,1], and the not-a-knot end condition. In this paper, we provide details for the construction of sparse grids and our spline interpolants, and a demonstration of computational performance. The paper includes a formula for counting the grid points in sparse grids, and an estimate for the number of computations in computing sparse spline interpolants. The results show that our construction performs at the level we expect based on other methods in the literature.

Original languageEnglish
Title of host publicationApplied Mathematical Analysis and Computations II - 1st SGMC
EditorsDivine Wanduku, Shijun Zheng, Zhan Chen, Andrew Sills, Haomin Zhou, Ephraim Agyingi
PublisherSpringer
Pages285-299
Number of pages15
ISBN (Print)9783031697098
DOIs
StatePublished - 2024
Event1st Southern Georgia Mathematics Conference, SGMC 2021 - Virtual, Online
Duration: Apr 2 2021Apr 3 2021

Publication series

NameSpringer Proceedings in Mathematics and Statistics
Volume472
ISSN (Print)2194-1009
ISSN (Electronic)2194-1017

Conference

Conference1st Southern Georgia Mathematics Conference, SGMC 2021
CityVirtual, Online
Period04/2/2104/3/21

Scopus Subject Areas

  • General Mathematics

Keywords

  • Approximation
  • Interpolation
  • Sparse grids
  • Splines

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