Sparse grid approximation in weighted Wiener spaces

11/11/2021
by   Yurii Kolomoitsev, et al.
0

We study approximation properties of multivariate periodic functions from weighted Wiener spaces by sparse grids methods constructed with the help of quasi-interpolation operators. The class of such operators includes classical interpolation and sampling operators, Kantorovich-type operators, scaling expansions associated with wavelet constructions, and others. We obtain the rate of convergence of the corresponding sparse grids methods in weighted Wiener norms as well as analogues of the Littlewood-Paley-type characterizations in terms of families of quasi-interpolation operators.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/15/2020

Approximation by quasi-interpolation operators and Smolyak's algorithm

We study approximation of multivariate periodic functions from Besov and...
research
02/11/2020

Approximation properties of periodic multivariate quasi-interpolation operators

We study approximation properties of the general multivariate periodic q...
research
12/10/2021

Spaces of Besov-Sobolev type and a problem on nonlinear approximation

We study fractional variants of the quasi-norms introduced by Brezis, Va...
research
02/25/2022

Convergence of sparse grid Gaussian convolution approximation for multi-dimensional periodic function

We consider the problem of approximating [0,1]^d-periodic functions by c...
research
09/06/2023

High Accuracy Quasi-Interpolation using a new class of generalized Multiquadrics

A new generalization of multiquadric functions ϕ(x)=√(c^2d+||x||^2d), wh...
research
10/11/2019

B-Splines for Sparse Grids: Algorithms and Application to Higher-Dimensional Optimization

In simulation technology, computationally expensive objective functions ...

Please sign up or login with your details

Forgot password? Click here to reset