Detailed error analyses are given for sparse-grid function representations through the combination technique. Two- and three-dimensional, and smooth and discontinuous functions are considered, as well as piecewise-constant and piecewise-linear interpolation techniques. Where appropriate, the results of the analyses are verified in numerical experiments. Instead of the common vertex-based function representation, cell-centered function representation is considered. Explicit, pointwise error expressions for the representation error are given, rather than order estimates. The paper contributes to the theory of sparse-grid techniques
Sparse grids, combined with gradient penalties provide an attractive tool for regularised least squa...
Sparse grids, combined with gradient penalties provide an attractive tool for regularised least squa...
The combination technique has repeatedly been shown to be an effective tool for the approximation wi...
Detailed error analyses are given for sparse-grid function representations through the combination t...
Error analysis for function representation by the sparse-grid combination techniqu
We investigate a new way of choosing combination coefficients for the sparse grid combination techni...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
Functionals related to a solution of a problem, usually modelled by partial differential equations, ...
Summary. In this paper we present a locally and dimension-adaptive sparse grid method for interpolat...
AbstractIn the Sparse Point Representation (SPR) method the principle is to retain the function data...
textabstractIn this paper we describe methods to approximate functions and differential operators on...
Our goal is to present an elementary approach to the analysis and programming of sparse grid finite ...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
Sparse grids (Zenger, C. (1990) Sparse grids. Parallel Algorithms for Partial Differential Equations...
textabstractIn this paper, we give a unified approach to error estimates for interpolation on sparse...
Sparse grids, combined with gradient penalties provide an attractive tool for regularised least squa...
Sparse grids, combined with gradient penalties provide an attractive tool for regularised least squa...
The combination technique has repeatedly been shown to be an effective tool for the approximation wi...
Detailed error analyses are given for sparse-grid function representations through the combination t...
Error analysis for function representation by the sparse-grid combination techniqu
We investigate a new way of choosing combination coefficients for the sparse grid combination techni...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
Functionals related to a solution of a problem, usually modelled by partial differential equations, ...
Summary. In this paper we present a locally and dimension-adaptive sparse grid method for interpolat...
AbstractIn the Sparse Point Representation (SPR) method the principle is to retain the function data...
textabstractIn this paper we describe methods to approximate functions and differential operators on...
Our goal is to present an elementary approach to the analysis and programming of sparse grid finite ...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
Sparse grids (Zenger, C. (1990) Sparse grids. Parallel Algorithms for Partial Differential Equations...
textabstractIn this paper, we give a unified approach to error estimates for interpolation on sparse...
Sparse grids, combined with gradient penalties provide an attractive tool for regularised least squa...
Sparse grids, combined with gradient penalties provide an attractive tool for regularised least squa...
The combination technique has repeatedly been shown to be an effective tool for the approximation wi...