We discuss a pointwise numerical differentiation formula on multivariate scattered data, based on the coefficients of local polynomial interpolation at Discrete Leja Points, written in Taylor’s formula monomial basis. Error bounds for the approximation of partial derivatives of any order compatible with the function regularity are provided, as well as sensitivity estimates to functional perturbations, in terms of the inverse Vandermonde coefficients that are active in the differentiation process. Several numerical tests are presented showing the accuracy of the approximation
AbstractWe present an innovative method for multivariate numerical differentiation i.e. the estimati...
The aim of this paper is to extend the approximate quasi-interpolation on a uniform grid by dilated ...
For radial basis function interpolation of scattered data in IR d the approximative reproduction of ...
We discuss a pointwise numerical differentiation formula on multivariate scattered data, based on th...
We present an adaptive pointwise numerical differentiator on multivariate scattered data, based on l...
AbstractA class of multivariate scattered data interpolation methods which includes the so-called mu...
Abstract: We show how to derive error estimates between a function and its inter-polating polynomial...
We show how to derive error estimates between a function and its interpolating polynomial and betwe...
This paper describes a new computational approach to multivariate scattered data interpolation. It i...
This paper describes a new computational approach to multivariate scattered data interpolation. It i...
AbstractThis paper describes a new computational approach to multivariate scattered data interpolati...
AbstractQuasi-interpolation is an important tool, used both in theory and in practice, for the appro...
Abstract. Finite difference methods, such as the mid-point rule, have been applied successfully to t...
The application of widely known blending methods for constructing C1 bivariate functions interpolati...
The application of widely known blending methods for constructing C1 bivariate functions interpolati...
AbstractWe present an innovative method for multivariate numerical differentiation i.e. the estimati...
The aim of this paper is to extend the approximate quasi-interpolation on a uniform grid by dilated ...
For radial basis function interpolation of scattered data in IR d the approximative reproduction of ...
We discuss a pointwise numerical differentiation formula on multivariate scattered data, based on th...
We present an adaptive pointwise numerical differentiator on multivariate scattered data, based on l...
AbstractA class of multivariate scattered data interpolation methods which includes the so-called mu...
Abstract: We show how to derive error estimates between a function and its inter-polating polynomial...
We show how to derive error estimates between a function and its interpolating polynomial and betwe...
This paper describes a new computational approach to multivariate scattered data interpolation. It i...
This paper describes a new computational approach to multivariate scattered data interpolation. It i...
AbstractThis paper describes a new computational approach to multivariate scattered data interpolati...
AbstractQuasi-interpolation is an important tool, used both in theory and in practice, for the appro...
Abstract. Finite difference methods, such as the mid-point rule, have been applied successfully to t...
The application of widely known blending methods for constructing C1 bivariate functions interpolati...
The application of widely known blending methods for constructing C1 bivariate functions interpolati...
AbstractWe present an innovative method for multivariate numerical differentiation i.e. the estimati...
The aim of this paper is to extend the approximate quasi-interpolation on a uniform grid by dilated ...
For radial basis function interpolation of scattered data in IR d the approximative reproduction of ...