近似非光滑函数的混合算子及其在弱奇异核Volterra积分方程上的应用

IF 1.4 4区 数学 Q2 MATHEMATICS, APPLIED Numerical Functional Analysis and Optimization Pub Date : 2022-12-02 DOI:10.1080/01630563.2022.2150642
S. C. Buranay, M. A. Özarslan, S. S. Falahhesar
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引用次数: 2

摘要

摘要研究了用于逼近在初始点有无界导数的连续函数的混合正线性算子的一些理论和数值问题。这些算子是用修正的Bernstein-Kantorovich算子来定义的,其中n是正整数,是固定常数,并简化为经典的Bernstein-Kantorovich算子。为了说明所给混合算子的重要性和适用性,我们开发了一种算法来实现它们,用于求解第二类弱奇异核线性Volterra积分方程。此外,还利用正则化方法对第一类积分方程进行了应用。结果表明,该算法的数值实现简单,计算效率高,能准确逼近非光滑解。
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Hybrid Operators for Approximating Nonsmooth Functions and Applications on Volterra Integral Equations with Weakly Singular Kernels
Abstract This research concerns some theoretical and numerical aspects of hybrid positive linear operators for approximating continuous functions on that have unbounded derivatives at the initial point. These operators are defined by using Modified Bernstein–Kantorovich operators where n is positive integer, is a fixed constant and reduces to the classical Bernstein–Kantorivich operators when To show the importance and the applicability of the given hybrid operators we develop an algorithm which implements them for solving the second kind linear Volterra integral equations with weakly singular kernels. Furthermore, applications are also performed on first kind integral equations, by utilizing regularization. Eventually, it is shown that the numerical realization of the given algorithm is easy and computationally efficient and gives accurate approximations to nonsmooth solutions.
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来源期刊
CiteScore
2.40
自引率
8.30%
发文量
74
审稿时长
6-12 weeks
期刊介绍: Numerical Functional Analysis and Optimization is a journal aimed at development and applications of functional analysis and operator-theoretic methods in numerical analysis, optimization and approximation theory, control theory, signal and image processing, inverse and ill-posed problems, applied and computational harmonic analysis, operator equations, and nonlinear functional analysis. Not all high-quality papers within the union of these fields are within the scope of NFAO. Generalizations and abstractions that significantly advance their fields and reinforce the concrete by providing new insight and important results for problems arising from applications are welcome. On the other hand, technical generalizations for their own sake with window dressing about applications, or variants of known results and algorithms, are not suitable for this journal. Numerical Functional Analysis and Optimization publishes about 70 papers per year. It is our current policy to limit consideration to one submitted paper by any author/co-author per two consecutive years. Exception will be made for seminal papers.
期刊最新文献
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