In this paper, we present an algorithm for trigonometric interpolation of multivariate functions on generalized sparse grids and study its application for the approximation of functions in periodic Sobolev spaces of dominating mixed smoothness. In particular, we derive estimates for the error and the cost. We construct interpolants with a computational cost complexity which is substantially lower than for the standard full grid case. The associated generalized sparse grid interpolants have the same approximation order as the standard full grid interpolants, provided that certain additional regularity assumptions on the considered functions are fulfilled. Numerical results validate our theoretical findings
In this dissertation, it is first shown that, when the radial basis function is a $p$-norm and $1 2...
Nested spaces of multivariate functions on the square forming a nonstationary multiresolution analys...
Let q⩾1 be an integer, y_1,…,y_M∈[-π,π]^q, and η be the minimal separation among these points. Given...
To approximate smooth multivariate functions, sparse grid interpolation is superior to full tensor-p...
AbstractWe develop a fast discrete algorithm for computing the sparse Fourier expansion of a functio...
AbstractWe propose a periodic B-spline quasi-interpolation for multivariate functions on sparse grid...
A straightforward discretisation of high-dimensional problems often leads to a curse of dimensions a...
Sparse grid discretisations allow for a severe decrease in the number of degrees of freedom for high...
textabstractIn this paper, we give a unified approach to error estimates for interpolation on sparse...
AbstractSparse grid discretisations allow for a severe decrease in the number of degrees of freedom ...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
In this work, the fast evaluation and reconstruction of multivariate trigonometric polynomials with ...
In this paper we construct non-aliasing interpolation spaces and Lagrange functions for lattice grid...
A straightforward discretization of problems in d spatial dimensions often leads to an exponential g...
When working on multidimensional problems, the number of points needed when using a tensor product g...
In this dissertation, it is first shown that, when the radial basis function is a $p$-norm and $1 2...
Nested spaces of multivariate functions on the square forming a nonstationary multiresolution analys...
Let q⩾1 be an integer, y_1,…,y_M∈[-π,π]^q, and η be the minimal separation among these points. Given...
To approximate smooth multivariate functions, sparse grid interpolation is superior to full tensor-p...
AbstractWe develop a fast discrete algorithm for computing the sparse Fourier expansion of a functio...
AbstractWe propose a periodic B-spline quasi-interpolation for multivariate functions on sparse grid...
A straightforward discretisation of high-dimensional problems often leads to a curse of dimensions a...
Sparse grid discretisations allow for a severe decrease in the number of degrees of freedom for high...
textabstractIn this paper, we give a unified approach to error estimates for interpolation on sparse...
AbstractSparse grid discretisations allow for a severe decrease in the number of degrees of freedom ...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
In this work, the fast evaluation and reconstruction of multivariate trigonometric polynomials with ...
In this paper we construct non-aliasing interpolation spaces and Lagrange functions for lattice grid...
A straightforward discretization of problems in d spatial dimensions often leads to an exponential g...
When working on multidimensional problems, the number of points needed when using a tensor product g...
In this dissertation, it is first shown that, when the radial basis function is a $p$-norm and $1 2...
Nested spaces of multivariate functions on the square forming a nonstationary multiresolution analys...
Let q⩾1 be an integer, y_1,…,y_M∈[-π,π]^q, and η be the minimal separation among these points. Given...