Results 1 to 10 of about 3,893 (298)
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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Reproducing kernel functions for linear tenth-order boundary value problems [PDF]
ITM Web of Conferences, 2018 Higher order differential equations have always been an onerous problem to investigate for the mathematicians and engineers. Different numerical methods were applied to get numerical approximations of such problems.
Akgül Ali +3 more
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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
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Alexandria Engineering Journal, 2020 In this paper, on the basis of the reproducing kernel functions, a novel meshless algorithm is explored for fractional advection–diffusion-reaction equations (ADREs) with Caputo time variable order.
Xiuying Li, Boying Wu
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Reproducing kernel functions and homogenizing transforms
Thermal Science, 2021 A lot of problems of the physical world can be modeled by non-linear ODE with their initial and boundary conditions. Especially higher order differential equations play a vital role in this process. The method for solution and its effectiveness are as important as the modelling.
Elif Nuray Yıldırım, Ali Akgül
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New Reproducing Kernel Functions [PDF]
Mathematical Problems in Engineering, 2015 Some new reproducing kernel functions on time scales are presented. Reproducing kernel functions have not been found on time scales till now. These functions are very important on time scales and they will be very useful for researchers. We need these functions to solve dynamic equations on time scales with the reproducing kernel method.
Ali Akgül
+7 more sources
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
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Probability Error Bounds for Approximation of Functions in Reproducing Kernel Hilbert Spaces [PDF]
Journal of Function Spaces, 2021 We find probability error bounds for approximations of functions f in a separable reproducing kernel Hilbert space H with reproducing kernel K on a base space X, firstly in terms of finite linear combinations of functions of type Kxi and then in terms of
Ata Deniz Aydın, Aurelian Gheondea
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Representing systems of reproducing kernels in spaces of analytic functions [PDF]
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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Introducing the kernel descent optimizer for variational quantum algorithms [PDF]
Scientific ReportsIn recent years, variational quantum algorithms have garnered significant attention as a candidate approach for near-term quantum advantage using noisy intermediate-scale quantum (NISQ) devices.
Lars Simon, Holger Eble, Manuel Radons
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