New reproducing kernel functions in the reproducing kernel Sobolev spaces
AIMS Mathematics, 2020 In this paper we construct some new reproducing kernel functions in the reproducing kernel Sobolev space. These functions are new in the literature. We can solve many problems by these functions in the reproducing kernel Sobolev spaces.
Ali Akgül +2 more
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Optimal Approximation in Hilbert Spaces with Reproducing Kernel Functions [PDF]
Mathematics of Computation, 1970 Characterisations of optimal linear estimation rules are given in terms of the reproducing kernel function of a suitable Hilbert space. The results are illustrated by means of three different, useful function spaces, showing, among other things, how Gaussian quadrature rules, and the Whittaker Cardinal Function, relate to optimal linear estimation ...
F. M. Larkin
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Cyclicity in Reproducing Kernel Hilbert Spaces of Analytic Functions [PDF]
Computational Methods and Function Theory, 2014 We introduce a large family of reproducing kernel Hilbert spaces $\mathcal{H} \subset \mbox{Hol}(\mathbb{D})$, which include the classical Dirichlet-type spaces $\mathcal{D}_ $, by requiring normalized monomials to form a Riesz basis for $\mathcal{H}$.
Emmanuel Fricain +2 more
openalex +7 more sources
Reproducing kernel functions for the generalized Kuramoto-Sivashinsky equation [PDF]
ITM Web of Conferences, 2018 Reproducing kernel functions are obtained for the solution of generalized Kuramoto–Sivashinsky (GKS) equation in this paper. These reproducing kernel functions are valuable in the reproducing kernel Hilbert space method.
Akgül Ali +3 more
doaj +3 more sources
A reproducing kernel space model for 𝐍_{𝜅}-functions [PDF]
Proceedings of the American Mathematical Society, 2003 A new model for generalized Nevanlinna functions Q ∈ N κ Q\in \mathbf {N}_\kappa will be presented. It involves Bezoutians and companion operators associated with certain polynomials determined by the generalized zeros and poles of Q Q .
Vladimir Derkach, Seppo Hassi
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Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations
, 2015 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 which can be ...
Fukumizu, K. +4 more
core +3 more sources
Representing systems of reproducing kernels in spaces of analytic functions
Results in Mathematics, 2022 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.
Anton Baranov, Timur Batenev
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Series Expansion and Reproducing Kernels for Hyperharmonic Functions
Journal of Mathematical Analysis and Applications, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Miroljub Jevtić, Miroslav Pavlović
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Reproducing Kernel Hilbert Space and Coalescence Hidden-variable Fractal Interpolation Functions [PDF]
Demonstratio Mathematica, 2019 Reproducing Kernel Hilbert Spaces (RKHS) and their kernel are important tools which have been found to be incredibly useful in many areas like machine learning, complex analysis, probability theory, group representation theory and the theory of integral ...
Prasad Srijanani Anurag
doaj +2 more sources
Solving Support Vector Machines in Reproducing Kernel Banach Spaces with Positive Definite Functions
, 2013 In this paper we solve support vector machines in reproducing kernel Banach spaces with reproducing kernels defined on nonsymmetric domains instead of the traditional methods in reproducing kernel Hilbert spaces.
Adams +32 more
core +2 more sources