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The paper is devoted to discretization of integral norms of functions from a given finite dimensional subspace. This problem is very important in applications but there is no systematic study of it. We present here a new technique, which…

Numerical Analysis · Mathematics 2017-03-13 V. N. Temlyakov

The paper is devoted to discretization of integral norms of functions from a given finite dimensional subspace. We use recent general results on sampling discretization to derive a new Marcinkiewicz type discretization theorem for the…

Numerical Analysis · Mathematics 2020-05-14 Vladimir Temlyakov

This survey addresses sampling discretization and its connections with other areas of mathematics. The survey concentrates on sampling discretization of norms of elements of finite-dimensional subspaces. We present here known results on…

Functional Analysis · Mathematics 2022-02-11 B. Kashin , E. Kosov , I. Limonova , V. Temlyakov

The paper is devoted to discretization of integral norms of functions from a given finite dimensional subspace. Even though this problem is extremely important in applications, its systematic study has begun recently. In this paper we…

Classical Analysis and ODEs · Mathematics 2020-01-28 F. Dai , A. Prymak , A. Shadrin , V. Temlyakov , S. Tikhonov

Discretization of the uniform norm of functions from a given finite dimensional subspace of continuous functions is studied. We pay special attention to the case of trigonometric polynomials with frequencies from an arbitrary finite set…

Numerical Analysis · Mathematics 2021-12-14 Boris Kashin , Sergei Konyagin , Vladimir Temlyakov

The paper addresses a problem of sampling discretization of integral norms of elements of finite-dimensional subspaces satisfying some conditions. We prove sampling discretization results under a standard assumption formulated in terms of…

Functional Analysis · Mathematics 2023-04-13 F. Dai , E. Kosov , V. Temlyakov

The problem of replacing an integral norm with respect to a given probability measure by the corresponding integral norm with respect to a discrete measure is discussed in the paper. The above problem is studied for elements of finite…

Numerical Analysis · Mathematics 2019-11-01 F. Dai , A. Prymak , V. N. Temlyakov , S. Tikhonov

The paper studies the sampling discretization problem for integral norms on subspaces of $L^p(\mu)$. Several close to optimal results are obtained on subspaces for which certain Nikolskii-type inequality is valid. The problem of norms…

Functional Analysis · Mathematics 2021-03-11 Egor Kosov

Discretization of the uniform norm of functions from a given finite dimensional subspace of continuous functions is studied. Previous known results show that for any $N$-dimensional subspace of the space of continuous functions it is…

Functional Analysis · Mathematics 2024-05-08 E. D. Kosov , V. N. Temlyakov

The paper addresses the problem of sampling discretization of integral norms of elements of finite-dimensional subspaces satisfying some conditions. We prove sampling discretization results under two standard kinds of assumptions --…

Numerical Analysis · Mathematics 2021-09-21 F. Dai , V. Temlyakov

We consider infinitely dimensional classes of functions and instead of the relative error setting, which was used in previous papers on the integral norm discretization, we consider the absolute error setting. We demonstrate how known…

Numerical Analysis · Mathematics 2022-03-15 V. N. Temlyakov

The recovery of multivariate functions and estimating their integrals from finitely many samples is one of the central tasks in modern approximation theory. Marcinkiewicz--Zygmund inequalities provide answers to both the recovery and the…

Numerical Analysis · Mathematics 2023-03-02 Frank Filbir , Ralf Hielscher , Thomas Jahn , Tino Ullrich

This paper studies the behavior of the entropy numbers of classes of functions with bounded integral norms from a given finite dimensional linear subspace. Upper bounds of these entropy numbers in the uniform norm are obtained and applied…

Classical Analysis and ODEs · Mathematics 2020-01-30 F. Dai , A. Prymak , A. Shadrin , V. Temlyakov , S. Tikhonov

The paper is devoted to discretization of integral norms of functions from a given collection of finite dimensional subspaces. For natural collections of subspaces of the multivariate trigonometric polynomials we construct sets of points,…

Numerical Analysis · Mathematics 2017-08-30 V. N. Temlyakov

The main goal of this paper is to provide a brief survey of recent results which connect together results from different areas of research. It is well known that numerical integration of functions with mixed smoothness is closely related to…

Numerical Analysis · Mathematics 2018-12-12 Vladimir Temlyakov

Let $X_N$ be an $N$-dimensional subspace of $L_2$ functions on a probability space $(\Omega, \mu)$ spanned by a uniformly bounded Riesz basis $\Phi_N$. Given an integer $1\leq v\leq N$ and an exponent $1\leq q\leq 2$, we obtain universal…

Functional Analysis · Mathematics 2021-07-27 Feng Dai , V. Temlyakov

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…

Functional Analysis · Mathematics 2021-04-23 Irina Limonova , Vladimir Temlyakov

Recently, it was discovered that for a given function class $\mathbf{F}$ the error of best linear recovery in the square norm can be bounded above by the Kolmogorov width of $\mathbf{F}$ in the uniform norm. That analysis is based on deep…

Numerical Analysis · Mathematics 2023-05-17 F. Dai , V. Temlyakov

We study the relationship between sampling sequences in infinite dimensional Hilbert spaces of analytic functions and Marcinkiewicz-Zygmund inequalities in subspaces of polynomials. We focus on the study of the Hardy space and the Bergman…

Complex Variables · Mathematics 2023-04-18 Karlheinz Gröchenig , Joaquim Ortega-Cerdà

We obtain new sampling discretization results in Orlicz norms on finite dimensional spaces. As applications, we study sampling recovery problems, where the error of the recovery process is calculated with respect to different Orlicz norms.…

Functional Analysis · Mathematics 2024-08-27 Egor Kosov , Sergey Tikhonov
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