A Family of Newton Type Iterative Methods for Solving Nonlinear Equations

被引:10
|
作者
Wang, Xiaofeng [1 ]
Qin, Yuping [2 ]
Qian, Weiyi [1 ]
Zhang, Sheng [1 ]
Fan, Xiaodong [1 ]
机构
[1] Bohai Univ, Sch Math & Phys, Jinzhou 121013, Peoples R China
[2] Bohai Univ, Coll Engn, Jinzhou 121013, Peoples R China
来源
ALGORITHMS | 2015年 / 8卷 / 03期
基金
中国国家自然科学基金;
关键词
multipoint iterative methods; nonlinear equations; R-order convergence; root-finding methods;
D O I
10.3390/a8030786
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a general family of n-point Newton type iterative methods for solving nonlinear equations is constructed by using direct Hermite interpolation. The order of convergence of the new n-point iterative methods without memory is 2(n) requiring the evaluations of n functions and one first-order derivative in per full iteration, which implies that this family is optimal according to Kung and Traub's conjecture (1974). Its error equations and asymptotic convergence constants are obtained. The n-point iterative methods with memory are obtained by using a self-accelerating parameter, which achieve much faster convergence than the corresponding n-point methods without memory. The increase of convergence order is attained without any additional calculations so that the n-point Newton type iterative methods with memory possess a very high computational efficiency. Numerical examples are demonstrated to confirm theoretical results.
引用
收藏
页码:786 / 798
页数:13
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