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The Hua-Radon and polarized Hua-Radon transform are two orthogonal projections defined on holomorphic functions in the Lie sphere. Both transformations can be written as integral transforms with respect to a suitable reproducing kernel.…

Classical Analysis and ODEs · Mathematics 2021-05-07 Teppo Mertens , Frank Sommen

In this article, we derive off-diagonal estimates of the Bergman kernel associated to the tensor-powers of the cotangent bundle defined on a hyperbolic Riemann surface of finite volume, when the distance between the points is less than…

Complex Variables · Mathematics 2018-08-15 Anilatmaja Aryasomayajula , Priyanka Majumder

We consider mixed normed Bergman spaces on homogeneous Siegel domains. In the literature, two different approaches have been considered and several results seem difficult to be compared. In this paper we compare the results available in the…

Complex Variables · Mathematics 2023-11-13 Mattia Calzi , Marco M. Peloso

By making a seminal use of the maximum modulus principle of holomorphic functions we prove existence of $n$-best kernel approximation for a wide class of reproducing kernel Hilbert spaces of holomorphic functions in the unit disc, and for…

Complex Variables · Mathematics 2022-01-20 Tao Qian

Kernels for structured data are commonly obtained by decomposing objects into their parts and adding up the similarities between all pairs of parts measured by a base kernel. Assignment kernels are based on an optimal bijection between the…

Machine Learning · Computer Science 2019-08-20 Nils M. Kriege

Kernel approximation with exponentials is useful in many problems with convolution quadrature and particle interactions such as integral-differential equations, molecular dynamics and machine learning. This paper proposes a weighted…

Computational Physics · Physics 2025-05-07 Yuanshen Lin , Zhenli Xu , Yusu Zhang , Qi Zhou

We present a framework for reconstructing any simply connected, bounded or unbounded, quadrature domain $\Omega$ from its quadrature function $h$. Using the Faber transform, we derive formulae directly relating $h$ to the Riemann map for…

Complex Variables · Mathematics 2025-12-30 Andrew J. Graven , Nikolai G. Makarov

We develop a coordinate-free probabilistic framework for determinantal point processes associated with Bergman kernels on compact complex manifolds. The basic issue is that Bergman kernels are naturally line-bundle-valued:…

Complex Variables · Mathematics 2026-05-27 Thibaut Lemoine

The Fourier transform and its inverse are well-known to have complex conjugate integral kernels. S.~Saitoh demonstrated that this relationship extends to the theory of integral transforms of Hilbert spaces of functions under certain…

Functional Analysis · Mathematics 2024-12-30 Akira Yamada

To help understand various reproducing kernels used in applied sciences, we investigate the inclusion relation of two reproducing kernel Hilbert spaces. Characterizations in terms of feature maps of the corresponding reproducing kernels are…

Functional Analysis · Mathematics 2011-06-22 Haizhang Zhang , Liang Zhao

A simple example of an $n$-dimensional admissible complex of planes is given for the overdetermined $k$-plane transform in $\mathbb{R}^n$. For the corresponding restricted $k$-plane transform sharp existence conditions are obtained and…

Functional Analysis · Mathematics 2013-12-02 Boris Rubin

In this paper we investigate the Bergman kernel function for intersection of two complex ellipsoids $\{(z,w_1,w_2) \in \mathbb{C}^{n+2} : |z_1|^2 + \cdots + |z_n|^2 + |w_1|^q < 1, \quad |z_1|^2 + \cdots + |z_n|^2 + |w_2|^r < 1\}.$

Complex Variables · Mathematics 2016-01-13 Tomasz Beberok

In this paper we consider the reproducing kernel thesis for boundedness and compactness for operators on $\ell^2$--valued Bergman-type spaces. This paper generalizes many well--known results about classical function spaces to their…

Classical Analysis and ODEs · Mathematics 2015-05-21 Robert Rahm

In this paper we construct a hierarchy of multivariate polynomial approximation kernels via semidefinite programming. We give details on the implementation of the semidefinite programs defining the kernels. Finally, we show how a symmetry…

Optimization and Control · Mathematics 2023-07-19 Felix Kirschner , Etienne de Klerk

We propose a novel adaptive kernel based regression method for complex-valued signals: the generalized complex-valued kernel least-mean-square (gCKLMS). We borrow from the new results on widely linear reproducing kernel Hilbert space…

Machine Learning · Statistics 2019-10-02 Rafael Boloix-Tortosa , Juan José Murillo-Fuentes , Sotirios A. Tsaftaris

We show how to express a conformal map of a general two connected domain in the plane such that neither boundary component is a point to a representative domain which has the virtue of having an explicit algebraic Bergman kernel function.…

Complex Variables · Mathematics 2008-01-16 Steven R. Bell , Ersin Deger , Thomas Tegtmeyer

In this manuscript, we obtain a plane wave decomposition for the delta distribution in superspace, provided that the superdimension is not odd and negative. This decomposition allows for explicit inversion formulas for the super Radon…

Mathematical Physics · Physics 2021-07-13 Alí Guzmán Adán , Irene Sabadini , Frank Sommen

Weighted discrete Hilbert transforms $(a_n)_n \mapsto \sum_n a_n v_n/(z-\gamma_n)$ from $\ell^2_v$ to a weighted $L^2$ space are studied, with $\Gamma=(\gamma_n)$ a sequence of distinct points in the complex plane and $v=(v_n)$ a…

Complex Variables · Mathematics 2014-12-10 Yurii Belov , Tesfa Y. Mengestie , Kristian Seip

We prove optimal estimates of the Bergman and Szeg\H{o} kernels on the diagonal, and the Bergman metric near the boundary of bounded smooth generalized decoupled pseudoconvex domains in $\mathbb{C}^n$. The generalized decoupled domains we…

Complex Variables · Mathematics 2023-12-21 Ravi Shankar Jaiswal

We extend the diffusion-map formalism to data sets that are induced by asymmetric kernels. Analytical convergence results of the resulting expansion are proved, and an algorithm is proposed to perform the dimensional reduction. In this work…

Machine Learning · Computer Science 2024-01-24 Alvaro Almeida Gomez , Antonio Silva Neto , Jorge zubelli