3 citations · 4 across the 6 of their papers we have counts for
6 papers · 1 filter
Global and explicit approximation of piecewise smooth 2D functions from cell-average data
Sergio Amat, David Levin, Juan Ruiz-Alvarez +1
Given cell-average data values of a piecewise smooth bivariate function within a domain , we look for a piecewise adaptive approximation to . We are interested in an expl…
Manifold Repairing, Reconstruction and Denoising from Scattered Data in High-Dimension
Shira Faigenbaum-Golovin, David Levin
We consider a problem of great practical interest: the repairing and recovery of a low-dimensional manifold embedded in high-dimensional space from noisy scattered data. Suppose th…
Approximation of Functions on Manifolds in High Dimension from Noisy Scattered Data
Shira Faigenbaum-Golovin, David Levin
In this paper, we consider the fundamental problem of approximation of functions on a low-dimensional manifold embedded in a high-dimensional space, with noise affecting both in th…
Corrected approximation strategy for piecewise smooth bivariate functions
Sergio Amat, David Levin, Juan Ruiz-Álvarez
Given values of a piecewise smooth function on a square grid within a domain , we look for a piecewise adaptive approximation to . Standard approximation techniques achie…
On a regularization-correction approach for the approximation of piecewise smooth functions
Sergio Amat, David Levin, Juan Ruiz-Álvarez
Linear approximation approaches suffer from Gibbs oscillations when approximating functions with singularities. ENO-SR resolution is a local approach avoiding oscillations and with…
Reconstruction of piecewise-smooth multivariate functions from Fourier data
David Levin
In some applications, one is interested in reconstructing a function from its Fourier series coefficients. The problem is that the Fourier series is slowly convergent if the fu…