Results 31 to 40 of about 1,638 (210)
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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A new kernel method for the uniform approximation in reproducing kernel Hilbert spaces
Applied Mathematics LettersThis paper discussed the uniform approximation of functions on reproducing kernel Hilbert spaces (RKHS). In this direction, classical approximation methods are investigated by Fourier orthogonal projections (assuming that the Fourier coefficients are given) and their discrete versions (assuming that function values are well-distributed).
Woula Themistoclakis, Marc Van Barel
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Reproducing kernel functions for the generalized Kuramoto-Sivashinsky equation
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
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Journal of Telecommunications and Information Technology, 2021 Among all the techniques combining multi-carrier modulation and spread spectrum, the multi-carrier code division multiple access (MC-CDMA) system is by far the most widely studied.
Rachid Fateh, Anouar Darif, Said Safi
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Adaptive Kernel Learning Kalman Filtering With Application to Model-Free Maneuvering Target Tracking
IEEE Access, 2022 Kernel method is a non-parametric linearization method for system modeling, which uses nonlinear projection from input data space to high-dimensional Hilbert feature space and employs kernel function for hiding the projection operator in a linear learner
Yuankai Li +5 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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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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Reproducing kernel functions for linear tenth-order boundary value problems
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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Advances in Difference Equations, 2021 This paper deals with the generalized Bagley–Torvik equation based on the concept of the Caputo–Fabrizio fractional derivative using a modified reproducing kernel Hilbert space treatment.
Shatha Hasan +5 more
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Approximations of the Reproducing Kernel Hilbert Space (RKHS) Embedding Method over Manifolds [PDF]
2020 59th IEEE Conference on Decision and Control (CDC), 2020 The reproducing kernel Hilbert space (RKHS) embedding method is a recently introduced estimation approach that seeks to identify the unknown or uncertain function in the governing equations of a nonlinear set of ordinary differential equations (ODEs). While the original state estimate evolves in Euclidean space, the function estimate is constructed in ...
Guo, Jia +2 more
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