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Certain relations between the Fourier transform of a function of bounded variation and the Hilbert transform of its derivative are revealed. The widest subspaces of the space of functions of bounded variation are indicated in which the…

Classical Analysis and ODEs · Mathematics 2012-01-27 E. Liflyand

This paper studies the probabilistic function approximation problem over reproducing kernel Hilbert spaces. We show the existence and uniqueness of the optimizer under mild assumptions. Furthermore, we generalize the celebrated representer…

Functional Analysis · Mathematics 2025-07-16 Dongwei Chen , Kai-Hsiang Wang

In this paper, we study multivariate approximation defined over weighted anisotropic Sobolev spaces which depend on two sequences ${\bf a}=\{a_j\}_{j\geq1}$ and ${\bf b}=\{b_j\}_{j\geq1}$ of positive numbers. We obtain strong equivalences…

Numerical Analysis · Mathematics 2019-07-02 JiDong Hao , Heping Wang

We consider multivariate approximation problems in the average case setting with a zero mean Gaussian measure whose covariance kernel is a periodic Gevrey kernel. We investigate various notions of algebraic tractability and exponential…

Numerical Analysis · Mathematics 2024-12-20 Wanting Lu , Heping Wang

In this paper, we investigate properties of a reproducing kernel Hilbert space of a group action. In particular, we introduce an equivalence relation on a compact Hausdorff space $X$, and consequently establish three equivalent definitions…

Functional Analysis · Mathematics 2025-04-16 Tyler Blom , Samuel A. Hokamp , Alejandro Jimenez , Jacob Laubacher

Herein, the theory of Bergman kernel is developed to the weighted case. A general form of weighted Bergman reproducing kernel is obtained, by which we can calculate concrete Bergman kernel functions for specific weights and domains.

Complex Variables · Mathematics 2020-09-08 Guan-Tie Deng , Yun Huang , Tao Qian

We suppose that $G$ is a locally compact abelian group, $Y$ is a measure space, and $H$ is a reproducing kernel Hilbert space on $G\times Y$ such that $H$ is naturally embedded into $L^2(G\times Y)$ and it is invariant under the…

Operator Algebras · Mathematics 2025-04-29 Shubham R. Bais , Egor A. Maximenko , D. Venku Naidu

Given a function $b$, holomorphic on the disc and bounded by 1, one can construct an associated reproducing kernel Hilbert space called the de Branges--Rovnyak space $H(b)$. We explore representations of such spaces via descriptions of the…

Complex Variables · Mathematics 2026-03-04 Eugenio Dellepiane , Daniel Seco

Reproducing kernel Hilbert spaces (RKHSs) are special Hilbert spaces where all the evaluation functionals are linear and bounded. They are in one-to-one correspondence with positive definite maps called kernels. Stable RKHSs enjoy the…

Systems and Control · Electrical Eng. & Systems 2023-05-04 Mauro Bisiacco , Gianluigi Pillonetto

We study the stability properties of nonlinear multi-task regression in reproducing Hilbert spaces with operator-valued kernels. Such kernels, a.k.a. multi-task kernels, are appropriate for learning prob- lems with nonscalar outputs like…

Machine Learning · Computer Science 2013-06-18 Julien Audiffren , Hachem Kadri

We study $d$-variate problem in the average case setting with respect to a zero-mean Gaussian measure. The covariance kernel of this Gaussian measure is a product of univariate kernels and satisfies some special properties. We study $(s,…

Numerical Analysis · Mathematics 2018-02-07 Jia Chen , Heping Wang , Jie Zhang

Sub-Bergman Hilbert spaces are analogues of de Branges-Rovnyak spaces in the Bergman space setting. They are reproducing kernel Hilbert spaces contractively contained in the Bergman space of the unit disk. K. Zhu analyzed sub-Bergman…

Functional Analysis · Mathematics 2018-11-16 Cheng Chu

In this note, we prove that the following function space with absolutely convergent Fourier series \[ F_d:=\left\{ f\in L^2([0,1)^d)\:\middle| \: \|f\|:=\sum_{\boldsymbol{k}\in \mathbb{Z}^d}|\hat{f}(\boldsymbol{k})| \max\left(1,\min_{j\in…

Numerical Analysis · Mathematics 2023-06-28 Takashi Goda

Some reverses of the continuous triangle inequality for Bochner integral of vector-valued functions in Hilbert spaces are given. Applications for complex-valued functions are provided as well.

Functional Analysis · Mathematics 2007-05-23 Sever Silvestru Dragomir

In this note, we describe the backward shift invariant subspaces for a large class of reproducing kernel Hilbert spaces. This class includes in particular de Branges-Rovnyak spaces (the non-extreme case) and the range space of co-analytic…

Functional Analysis · Mathematics 2019-04-08 Emmanuel Fricain , Javad Mashreghi , Rishika Rupam

The study presents a vector-valued extension of the classical Mercer theorem within the framework of reproducing kernel Hilbert spaces defined over Kaplansky-Hilbert modules associated with the algebra of essentially bounded measurable…

Functional Analysis · Mathematics 2025-11-24 A. Arziev , K. Kudaybergenov. P. Orinbaev

We discuss, within the simplified context provided by the polymeric harmonic oscillator, a construction leading to a separable Hilbert space that preserves some of the most important features of the spectrum of the Hamiltonian operator.…

General Relativity and Quantum Cosmology · Physics 2016-08-11 J. Fernando Barbero G. , Tomasz Pawłowski , Eduardo J. S. Villaseñor

A complete characterization of Hilbert space operators that generate weakly amenable algebras remains open, even in the case of compact operator. Farenick, Forrest and Marcoux proposed the question that if $T$ is a compact weakly amenable…

Functional Analysis · Mathematics 2010-09-01 Luo Yi Shi , YU Jing Wu , You Qing Ji

This is a survey article on Mercer's Theorem in its most general form and its relations with the theory of reproducing kernel Hilbert spaces and the spectral theory of compact operators. We provide a modern introduction to the basics of the…

Functional Analysis · Mathematics 2025-12-09 Aurelian Gheondea

The polynomial kernels are widely used in machine learning and they are one of the default choices to develop kernel-based classification and regression models. However, they are rarely used and considered in numerical analysis due to their…

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