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We consider divergence form elliptic operators L = - div A(x)\nabla, defined in the half space R^{n+1}_+, n \geq 2, where the coefficient matrix A(x) is bounded, measurable, uniformly elliptic, t-independent, and not necessarily symmetric.…

Analysis of PDEs · Mathematics 2012-02-14 Steve Hofmann , Carlos Kenig , Svitlana Mayboroda , Jill Pipher

We consider the approximation of manifold-valued functions by embedding the manifold into a higher dimensional space, applying a vector-valued approximation operator and projecting the resulting vector back to the manifold. It is well known…

Numerical Analysis · Mathematics 2022-10-24 Ralf Hielscher , Laura Lippert

We provide a novel transcription of monotone operator theory to the non-Euclidean finite-dimensional spaces $\ell_1$ and $\ell_{\infty}$. We first establish properties of mappings which are monotone with respect to the non-Euclidean norms…

Optimization and Control · Mathematics 2023-03-21 Alexander Davydov , Saber Jafarpour , Anton V. Proskurnikov , Francesco Bullo

Given a function dictionary $\cal D$ and an approximation budget $N\in\mathbb{N}^+$, nonlinear approximation seeks the linear combination of the best $N$ terms $\{T_n\}_{1\le n\le N}\subseteq{\cal D}$ to approximate a given function $f$…

Machine Learning · Computer Science 2020-11-06 Zuowei Shen , Haizhao Yang , Shijun Zhang

In this paper we consider asymmetric truncated Toeplitz operators acting between two finite-dimensional model spaces. We compute the dimension of the space of all such operators. We also describe the matrix representations of asymmetric…

Functional Analysis · Mathematics 2018-07-09 Joanna Jurasik , Bartosz Łanucha

This paper investigates the approximation properties of deep neural networks with piecewise-polynomial activation functions. We derive the required depth, width, and sparsity of a deep neural network to approximate any H\"{o}lder smooth…

Numerical Analysis · Mathematics 2022-12-06 Denis Belomestny , Alexey Naumov , Nikita Puchkin , Sergey Samsonov

We introduce certain linear positive operators and study some approximation properties of these operators in the space of functions, continuous on a compact set, of two variables. We also find the order of this approximation by using…

Classical Analysis and ODEs · Mathematics 2007-09-24 Fatma Tasdelen , Ali Olgun , Gulen Bascanbaz-Tunca

We study approximation by arbitrary linear combinations of $n$ translates of a single function of periodic functions. We construct some methods of this approximation for functions in a class induced by the convolution with a given function,…

Numerical Analysis · Mathematics 2017-03-01 Dinh Dũng , Charles A. Micchelli , Vu Nhat Huy

In this paper an asymmetrical operator of generalised translation is introduced, the generalised modulus of smoothness is defined by its means and the direct and inverse theorems in approximation theory are proved for that modulus. ----- V…

Functional Analysis · Mathematics 2012-09-03 Mikhail K. Potapov , Faton M. Berisha

In this paper, we analyze metrical approximations of functions $F :\Lambda times X \rightarrow Y$ by trigonometric polynomials and $\rho$-periodic type functions, where $\emptyset \neq \Lambda \subseteq {\mathbb R}^{n},$ $X$ and $Y $are…

Functional Analysis · Mathematics 2022-05-19 B. Chaouchi , M. Kostic , D. Velinov

We consider the order of convergence for linear and nonlinear Monte Carlo approximation of compact embeddings from Sobolev spaces of dominating mixed smoothness defined on the torus $\mathbb{T}^d$ into the space $L_{\infty}(\mathbb{T}^d)$…

Numerical Analysis · Mathematics 2018-03-02 Glenn Byrenheid , Robert J. Kunsch , Van Kien Nguyen

We describe the set of parameters $(p_1,p_2,q_1,q_2)$ such that the balls $B_{q_1,q_2}^{s,b}$ are rigid in $\ell_{q_1,q_2}^{s,b}$ metric i.e. they are poorly approximated by linear subspaces of dimension $\le (1-\varepsilon)sb$, for large…

Functional Analysis · Mathematics 2025-02-28 Yuri Malykhin , Konstantin Ryutin

In \cite{cheung2019optimally}, the authors presented two finite element methods for approximating second order boundary value problems on polytopial meshes with optimal accuracy without having to utilize curvilinear mappings. This was done…

Numerical Analysis · Mathematics 2023-01-11 James Cheung

We establish in this work approximation results of deep neural networks for smooth functions measured in Sobolev norms, motivated by recent development of numerical solvers for partial differential equations using deep neural networks. {Our…

Numerical Analysis · Mathematics 2022-07-25 Sean Hon , Haizhao Yang

We consider the problem of approximating a subset $M$ of a Hilbert space $X$ by a low-dimensional manifold $M_n$, using samples from $M$. We propose a nonlinear approximation method where $M_n $ is defined as the range of a smooth nonlinear…

Numerical Analysis · Mathematics 2025-11-20 Antoine Bensalah , Anthony Nouy , Joel Soffo

We identify the optimal range of the Calder\`{o}n operator and that of the classical Hilbert transform in the class of symmetric quasi-Banach spaces. Further consequences of our approach concern the optimal range of the triangular…

Functional Analysis · Mathematics 2019-08-27 F. Sukochev , K. Tulenov , D. Zanin

Let T : Lp --> Lp be a contraction, with p strictly between 1 and infinity, and assume that T is analytic, that is, there exists a constant K such that n\norm{T^n-T^{n-1}} < K for any positive integer n. Under the assumption that T is…

Functional Analysis · Mathematics 2014-02-26 Christian Le Merdy , Quanhua Xu

This paper deals with the approximation of discrete real-valued functions by first-degree splines (broken lines) with free knots for arbitrary $L_p$-norms ($1 \leq p \leq \infty)$. We prove the existence of best approximations und derive…

Numerical Analysis · Mathematics 2017-04-20 Ludwig J. Cromme , Jens Kunath

We characterize the best coapproximation(s) to a given matrix $ T $ out of a given subspace $ \mathbb{Y} $ of the space of diagonal matrices $ \mathcal{D}_n $, by using Birkhoff-James orthogonality techniques and with the help of a newly…

Functional Analysis · Mathematics 2024-08-23 Debmalya Sain , Shamim Sohel , Souvik Ghosh , Kallol Paul

The extension of the concept of $p-$summability for linear operators to the context of Lipschitz operators on metric spaces has been extensively studied in recent years. This research primarily uses the linearization of the metric space $M$…

Functional Analysis · Mathematics 2024-10-29 R. Arnau , E. A. Sánchez Pérez , S. Sanjuan
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