论巴拿赫空间中特劳布-斯特芬森类型方法的某些扩展

Bhavna, Saurabh Bhatia
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引用次数: 0

摘要

在本研究中,我们构建了一个无记忆的六阶无导数族,用于求解巴拿赫空间中的非线性算子方程。我们进一步将其修改为有记忆的九阶族,无需任何额外的函数评估。我们对这两种方法的局部收敛分析进行了研究,只使用了对一阶导数的假设。数值计算验证了理论结果,并表明我们的方法优于现有方法。此外,还提出了吸引力盆地,以了解所提议方法的动态行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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On some extension of Traub–Steffensen type methods in Banach spaces

In the present work, we construct a sixth order derivative free family without memory for solving nonlinear operator equations in Banach spaces. We further modify this to a ninth order family with memory without any additional functional evaluation. Local convergence analysis of both these methods have been studied using assumptions only on the first derivative. Numerical computations validate the theoretical results and show the superiority of our methods over the existing ones. Basins of attraction have also been presented to see the dynamical behaviour of the proposed methods.

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来源期刊
自引率
11.50%
发文量
352
期刊介绍: Computational & Applied Mathematics began to be published in 1981. This journal was conceived as the main scientific publication of SBMAC (Brazilian Society of Computational and Applied Mathematics). The objective of the journal is the publication of original research in Applied and Computational Mathematics, with interfaces in Physics, Engineering, Chemistry, Biology, Operations Research, Statistics, Social Sciences and Economy. The journal has the usual quality standards of scientific international journals and we aim high level of contributions in terms of originality, depth and relevance.
期刊最新文献
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