High order approximation to non-smooth multivariate functions

Anat Amir*, David Levin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Common approximation tools return low-order approximations in the vicinities of singularities. Most prior works solve this problem for univariate functions. In this work we introduce a method for approximating non-smooth multivariate functions of the form f=g+r+ where g,r∈CM+1(Rn) and the function r+ is defined by r+(y)={r(y),r(y)≥00,r(y)<0,∀y∈Rn. Given scattered (or uniform) data points X⊂Rn, we investigate approximation by quasi-interpolation. We design a correction term, such that the corrected approximation achieves full approximation order on the entire domain. We also show that the correction term is the solution to a Moving Least Squares (MLS) problem, and as such can both be easily computed and is smooth. Last, we prove that the suggested method includes a high-order approximation to the locations of the singularities.

Original languageEnglish
Pages (from-to)31-65
Number of pages35
JournalComputer Aided Geometric Design
StatePublished - Jul 2018


  • Multivariate functions
  • Non-smooth functions
  • Quasi-interpolation


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