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Reproducing Kernel Method for Solving Nonlinear Differential‐Difference Equations

Reproducing kernel method for solving nonlinear differential-difference equations
Authors: Reza Mokhtari; Fereshteh Toutian Isfahani; Maryam Mohammadi;

Reproducing Kernel Method for Solving Nonlinear Differential‐Difference Equations

Abstract

On the basis of reproducing kernel Hilbert spaces theory, an iterative algorithm for solving some nonlinear differential‐difference equations (NDDEs) is presented. The analytical solution is shown in a series form in a reproducing kernel space, and the approximate solution un,m is constructed by truncating the series to m terms. The convergence of un,m to the analytical solution is also proved. Results obtained by the proposed method imply that it can be considered as a simple and accurate method for solving such differential‐difference problems.

Country
Italy
Related Organizations
Keywords

convergence, Theoretical approximation of solutions to functional-differential equations, QA1-939, Analytical theory of ordinary differential equations: series, transformations, transforms, operational calculus, etc., nonlinear differential-difference equations, reproducing kernel Hilbert space, Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Average
Top 10%
Top 10%
Green
gold