Results 41 to 50 of about 4,141 (227)
Probability Error Bounds for Approximation of Functions in Reproducing Kernel Hilbert Spaces
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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Mathematical Modelling and Analysis, 2018 Based on the reproducing kernel Hilbert space method, a new approach is proposed to approximate the solution of the Black-Scholes equation with Dirichlet boundary conditions and introduce the reproducing kernel properties in which the initial conditions ...
Mohammadreza Foroutan +2 more
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Advanced Intelligent Discovery, EarlyView.The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
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New Numerical Method for Solving Tenth Order Boundary Value Problems
Mathematics, 2018 In this paper, we implement reproducing kernel Hilbert space method to tenth order boundary value problems. These problems are important for mathematicians. Different techniques were applied to get approximate solutions of such problems.
Ali Akgül +3 more
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Fractal and Fractional, 2020 In this research, obtaining of approximate solution for fractional-order Burgers’ equation will be presented in reproducing kernel Hilbert space (RKHS). Some special reproducing kernel spaces are identified according to inner products and norms.
Onur Saldır +2 more
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Journal of Mathematics, 2022 In this article, the reproducing kernel method is presented for the fractional differential equations with periodic conditions in the Hilbert space. This method gives an approximate solution to the problem.
Hoda Saky +2 more
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On the stability test for reproducing kernel Hilbert spaces
CoRR, 2023 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 additional property of containing only functions and absolutely integrable.
Mauro Bisiacco, Gianluigi Pillonetto
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Abstract and Applied Analysis, 2013 We investigate the effectiveness of reproducing kernel method (RKM) in solving partial differential equations. We propose a reproducing kernel method for solving the telegraph equation with initial and boundary conditions based on reproducing kernel ...
Mustafa Inc +2 more
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Advanced Intelligent Systems, EarlyView.Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
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Reproducing kernel Hilbert spaces on manifolds: Sobolev and diffusion spaces [PDF]
Analysis and Applications, 2020 We study reproducing kernel Hilbert spaces (RKHS) on a Riemannian manifold. In particular, we discuss under which condition Sobolev spaces are RKHS and characterize their reproducing kernels. Further, we introduce and discuss a class of smoother RKHS that we call diffusion spaces.
De Vito E., Mucke N., Rosasco L.
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