A generalisation of de la Vall\'ee-Poussin procedure to multivariate approximations

TL;DR

This paper extends the classical de la Vallée-Poussin approximation procedure from univariate to multivariate cases, allowing for more general basis functions beyond monomials, under certain assumptions.

Contribution

It introduces a generalized de la Vallée-Poussin procedure applicable to multivariate polynomial approximation with flexible basis functions.

Findings

The classical procedure can be extended to multivariate approximation.

The basis functions are not limited to monomials.

The extension relies on specific assumptions.

Abstract

The theory of Chebyshev approximation has been extensively studied. In most cases, the optimality conditions are based on the notion of alternance or alternating sequence (that is, maximal deviation points with alternating deviation signs). There are a number of approximation methods for polynomial and polynomial spline approximation. Some of them are based on the classical de la Vall\'ee-Poussin procedure. In this paper we demonstrate that under certain assumptions the classical de la Vall\'ee-Poussin procedure, developed for univariate polynomial approximation, can be extended to the case of multivariate approximation. The corresponding basis functions are not restricted to be monomials.