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In the Clifford algebra setting the present study develops three reproducing kernel Hilbert spaces of the Paley-Wiener type, namely the Paley-Wiener spaces, the Hardy spaces on strips, and the Bergman spaces on strips. In particular, we…

Complex Variables · Mathematics 2021-08-31 Pei Dang , Weixiong Mai , Tao Qian

Paragrassmann algebras are given a sesquilinear form for which one subalgebra becomes a Hilbert space known as the Segal-Bargmann space. This Hilbert space as well as the ambient space of the paragrassmann algebra itself are shown to have…

Mathematical Physics · Physics 2012-05-22 Stephen Bruce Sontz

Let $\{v_n\}$ be a complete minimal system in a Hilbert space $\mathcal{H}$ and let $\{w_m\}$ be its biorthogonal system. It is well known that $\{w_m\}$ is not necessarily complete. However the situation may change if we consider systems…

Complex Variables · Mathematics 2011-12-26 Anton Baranov , Yurii Belov

We describe a method to perform functional operations on probability distributions of random variables. The method uses reproducing kernel Hilbert space representations of probability distributions, and it is applicable to all operations…

Machine Learning · Statistics 2016-09-14 Bernhard Schölkopf , Krikamol Muandet , Kenji Fukumizu , Jonas Peters

Kernel interpolation is a fundamental technique for approximating functions from scattered data, with a well-understood convergence theory when interpolating elements of a reproducing kernel Hilbert space. Beyond this classical setting,…

Numerical Analysis · Mathematics 2025-05-19 Toni Karvonen , Gabriele Santin , Tizian Wenzel

Let $\nu$ be a rotation invariant Borel probability measure on the complex plane having moments of all orders. Given a positive integer $q$, it is proved that the space of $\nu$-square integrable $q$-analytic functions is the closure of…

Complex Variables · Mathematics 2019-01-08 Hicham Hachadi , El Hassan Youssfi

We give a simple proof of the so called reproducing kernel thesis for Hankel operators

Functional Analysis · Mathematics 2012-01-13 Sergei Treil

Motivated by the need of processing functional-valued data, or more general, operatorvalued data, we introduce the notion of the operator reproducing kernel Hilbert space (ORKHS). This space admits a unique operator reproducing kernel which…

Functional Analysis · Mathematics 2016-10-23 Rui Wang , Yuesheng Xu

In the present paper, we consider the integral operator, which acts in Hilbert space and has sine kernel. This operator generates two operator identities and two corresponding canonical differential systems. We find the asymptotics of the…

Classical Analysis and ODEs · Mathematics 2021-06-07 Lev Sakhnovich

In this paper, we study composition operators on Hilbert space of complex-valued harmonic functions. In particular, we explore isometries, the type of self-map that generate bounded composition operator, and characterize the boundedness of…

Functional Analysis · Mathematics 2025-03-14 Tseganesh Getachew Gebrehana , Hunduma Legesse Geleta

We give an elementary construction of representing systems of the Cauchy kernels in the Hardy spaces $H^p$, $1 \le p <\infty$, as well as of representing systems of reproducing kernels in weighted Hardy spaces.

Complex Variables · Mathematics 2023-04-13 Anton Baranov , Timur Batenev

We analyse the convergence of sampling algorithms for functions in reproducing kernel Hilbert spaces (RKHS). To this end, we discuss approximation properties of kernel regression under minimalistic assumptions on both the kernel and the…

Machine Learning · Statistics 2025-04-21 Armin Iske

Reproducing kernel Hilbert spaces (RKHSs) are special Hilbert spaces in one-to-one correspondence with positive definite maps called kernels. They are widely employed in machine learning to reconstruct unknown functions from sparse and…

Systems and Control · Electrical Eng. & Systems 2023-05-03 Mauro Bisiacco , Gianluigi Pillonetto

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…

The decomposition of polynomial spaces on unions of Grassmannians $\mathcal G_{{k_1},d}\cup\ldots\cup \mathcal G_{{k_r},d}$ into irreducible orthogonally invariant subspaces and their reproducing kernels are investigated. We also generalize…

Numerical Analysis · Mathematics 2018-05-17 Martin Ehler , Manuel Gräf

In this paper we investigate and compare different gradient algorithms designed for the domain expression of the shape derivative. Our main focus is to examine the usefulness of kernel reproducing Hilbert spaces for PDE constrained shape…

Optimization and Control · Mathematics 2016-04-20 Martin Eigel , Kevin Sturm

The spectral representation of the Wiener-Hopf operator K with kernel $1/{\pi}$ sinc is given determining explicitly the Hilbert space isomorphism, which transforms K into the multiplication operator by the identity on $L^2(0,1)$. Several…

Functional Analysis · Mathematics 2020-02-24 Domenico P. L. Castrigiano

We describe those reproducing kernel Hilbert spaces of holomorphic functions on domains in ${\Bbb C}^d$ for which an analogue of the Nevanlinna-Pick theorem holds, in other words when the existence of a (possibly matrix-valued) function in…

Functional Analysis · Mathematics 2016-10-07 Jim Agler , John E. McCarthy

This paper presents a bicomplex version of the Spectral Decomposition Theorem on infinite dimensional bicomplex Hilbert spaces. In the process, the ideas of bounded linear operators, orthogonal complements and compact operators on bicomplex…

Functional Analysis · Mathematics 2013-01-25 Kuldeep Singh Charak , Ravinder Kumar , Dominic Rochon

We present a method to construct a chain of reproducing kernel Hilbert spaces controlled by a first-order system of differential equations from a given unimodular function satisfying several conditions. One of the applications of that…

Functional Analysis · Mathematics 2025-10-21 Masatoshi Suzuki
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