Add to ORKGWhen working on multidimensional problems, the number of points needed when using a tensor product grid. This is known as the curse of dimensionality. In this thesis we propose a set of sparse grids, which can be used to dampen this curse. The grid is chosen such that we can apply the Fourier transform on functions sampeled on it. The thesis describes such an algorithm
Departing from Mulder's semi-coarsening technique for first-order PDEs, the notion of a grid of grid...
AbstractWe consider a simple approach for the fast evaluation of the Fourier transform of functions ...
This book deals with the numerical analysis and efficient numerical treatment of high-dimensional in...
When working on multidimensional problems, the number of points needed when using a tensor product g...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
In the recent decade, there has been growing interest in the numerical treatment of high-dimensional...
Abstract. Approximation problems in high dimensions arise in numerous applications such as problems ...
An O(NlogN) algorithm to Fourier transform sparse spatial data to sparse Fourier data is presented. ...
A multilevel algorithm that efficiently Fourier transforms sparse spatial data to sparse spectral da...
A straightforward discretisation of high-dimensional problems often leads to a curse of dimensions a...
An algorithm that efficiently Fourier transforms sparse spatial data to sparse spectral data with co...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
In this paper, we present an algorithm for trigonometric interpolation of multivariate functions on ...
AbstractWe develop a fast discrete algorithm for computing the sparse Fourier expansion of a functio...
Simple and practical algorithm for sparse fourier transform Citation Hassanieh, Haitham et al. "...
Departing from Mulder's semi-coarsening technique for first-order PDEs, the notion of a grid of grid...
AbstractWe consider a simple approach for the fast evaluation of the Fourier transform of functions ...
This book deals with the numerical analysis and efficient numerical treatment of high-dimensional in...
When working on multidimensional problems, the number of points needed when using a tensor product g...
The technique of sparse grids allows to overcome the curse of dimensionality, which prevents the use...
In the recent decade, there has been growing interest in the numerical treatment of high-dimensional...
Abstract. Approximation problems in high dimensions arise in numerous applications such as problems ...
An O(NlogN) algorithm to Fourier transform sparse spatial data to sparse Fourier data is presented. ...
A multilevel algorithm that efficiently Fourier transforms sparse spatial data to sparse spectral da...
A straightforward discretisation of high-dimensional problems often leads to a curse of dimensions a...
An algorithm that efficiently Fourier transforms sparse spatial data to sparse spectral data with co...
For the approximation of multidimensional functions, using classical numerical discretization scheme...
In this paper, we present an algorithm for trigonometric interpolation of multivariate functions on ...
AbstractWe develop a fast discrete algorithm for computing the sparse Fourier expansion of a functio...
Simple and practical algorithm for sparse fourier transform Citation Hassanieh, Haitham et al. "...
Departing from Mulder's semi-coarsening technique for first-order PDEs, the notion of a grid of grid...
AbstractWe consider a simple approach for the fast evaluation of the Fourier transform of functions ...
This book deals with the numerical analysis and efficient numerical treatment of high-dimensional in...