Lattice algorithms for multivariate \(L_{\infty}\) approximation in the worst-case setting

DOI10.1007/S00365-009-9075-XzbMath1182.65025OpenAlexW2099747558MaRDI QIDQ843730

Frances Y. Kuo, Grzegorz W. Wasilkowski, Henryk Woźniakowski

Publication date: 15 January 2010

Published in: Constructive Approximation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00365-009-9075-x

zbMATH Keywords

multivariate approximationlattice algorithms

Mathematics Subject Classification ID

Analysis of algorithms and problem complexity (68Q25) Abstract approximation theory (approximation in normed linear spaces and other abstract spaces) (41A65) Algorithms for approximation of functions (65D15) Approximation by arbitrary linear expressions (41A45)

Related Items (9)

\(\mathbb{L}_\infty\)-approximation in Korobov spaces with exponential weights ⋮ Tent-transformed lattice rules for integration and approximation of multivariate non-periodic functions ⋮ High-dimensional sparse FFT based on sampling along multiple rank-1 lattices ⋮ Tight error bounds for rank-1 lattice sampling in spaces of hybrid mixed smoothness ⋮ Rank-1 Lattices and Higher-Order Exponential Splitting for the Time-Dependent Schrödinger Equation ⋮ Multiple rank-1 lattices as sampling schemes for multivariate trigonometric polynomials ⋮ Function integration, reconstruction and approximation using rank-$1$ lattices ⋮ Approximation of multivariate periodic functions based on sampling along multiple rank-1 lattices ⋮ Strang Splitting in Combination with Rank-1 and Rank-r Lattices for the Time-Dependent Schrödinger Equation

Cites Work

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• On the power of standard information for weighted approximation

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