On sampling discretization in $L_2$

Abstract

We prove a sampling discretization theorem for the square norm of functions from a finite dimensional subspace satisfying Nikol'skii's inequality with an upper bound on the number of sampling points of the order of the dimension of the subspace

arXiv comment20 pages, presentation changed

Cited by in corpus (1)

• Optimal pointwise sampling for $L^2$ approximation