Results 31 to 40 of about 50,655 (282)

Generalized Jacobi reproducing kernel method in Hilbert spaces for solving the Black-Scholes option pricing problem arising in financial modelling

open access: yesMathematical 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
doaj   +1 more source

Reproducing kernel functions for the generalized Kuramoto-Sivashinsky equation

open access: yesITM 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   +1 more source

Cyclicity in Reproducing Kernel Hilbert Spaces of Analytic Functions [PDF]

open access: yesComputational 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 $\mathcal{H}$.
Fricain, Emmanuel   +2 more
openaire   +4 more sources

Reproducing kernel functions for linear tenth-order boundary value problems

open access: yesITM 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
doaj   +1 more source

Numerical Solution of Fractional Order Burgers’ Equation with Dirichlet and Neumann Boundary Conditions by Reproducing Kernel Method

open access: yesFractal 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
doaj   +1 more source

Reproducing kernel method for the solutions of non-linear partial differential equations

open access: yesArab Journal of Basic and Applied Sciences, 2021
In modeling of a lots of complex physical problems and engineering process, the non-linear partial differential equations have a very important role. Development of dependable and effective methods to solve such types equations are constructed.
Elif Nuray Yildirim   +2 more
doaj   +1 more source

Meshless Galerkin method based on RBFs and reproducing Kernel for quasi-linear parabolic equations with dirichlet boundary conditions

open access: yesMathematical Modelling and Analysis, 2021
The main aim of this paper is to present a hybrid scheme of both meshless Galerkin and reproducing kernel Hilbert space methods. The Galerkin meshless method is a powerful tool for solving a large class of multi-dimension problems.
Mehdi Mesrizadeh, Kamal Shanazari
doaj   +1 more source

Reproducing Kernel Hilbert Space vs. Frame Estimates

open access: yesMathematics, 2015
We consider conditions on a given system F of vectors in Hilbert space H, forming a frame, which turn H into a reproducing kernel Hilbert space. It is assumed that the vectors in F are functions on some set Ω .
Palle E. T. Jorgensen, Myung-Sin Song
doaj   +1 more source

Functionals with extrema at reproducing kernels

open access: yesGeometric and Functional Analysis, 2022
AbstractWe show that certain monotone functionals on the Hardy spaces and convex functionals on the Bergman spaces are maximized at the normalized reproducing kernels among the functions of norm 1, thus proving the contractivity conjecture of Pavlović and of Brevig, Ortega-Cerdà, Seip and Zhao and the Wehrl-type entropy conjecture for the SU(1, 1 ...
openaire   +4 more sources

Statistical properties of the method of regularization with periodic Gaussian reproducing kernel [PDF]

open access: yes, 2004
The method of regularization with the Gaussian reproducing kernel is popular in the machine learning literature and successful in many practical applications. In this paper we consider the periodic version of the Gaussian kernel regularization.
Brown, Lawrence D., Lin, Yi
core   +4 more sources

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