Elsevier

Journal of Approximation Theory

Volume 189, January 2015, Pages 137-159
Journal of Approximation Theory

Full length article
Multivariate Markov-type and Nikolskii-type inequalities for polynomials associated with downward closed multi-index sets

https://doi.org/10.1016/j.jat.2014.10.010Get rights and content
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Abstract

We present novel Markov-type and Nikolskii-type inequalities for multivariate polynomials associated with arbitrary downward closed multi-index sets in any dimension. Moreover, we show how the constant of these inequalities changes, when the polynomial is expanded in series of tensorized Legendre or Chebyshev or Gegenbauer or Jacobi orthogonal polynomials indexed by a downward closed multi-index set. The proofs of these inequalities rely on a general result concerning the summation of tensorized polynomials over arbitrary downward closed multi-index sets.

MSC

41A10
41A17

Keywords

Approximation theory
Multivariate polynomial approximation
Markov inequality
Nikolskii inequality
Orthogonal polynomials
Downward closed sets
Legendre polynomials
Chebyshev polynomials
Jacobi polynomials
Gegenbauer polynomials

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