Three-point methods with and without memory for solving nonlinear equations
作者:
Highlights:
•
摘要
A new family of three-point derivative free methods for solving nonlinear equations is presented. It is proved that the order of convergence of the basic family without memory is eight requiring four function-evaluations, which means that this family is optimal in the sense of the Kung–Traub conjecture. Further accelerations of convergence speed are attained by suitable variation of a free parameter in each iterative step. This self-accelerating parameter is calculated using information from the current and previous iteration so that the presented methods may be regarded as the methods with memory. The self-correcting parameter is calculated applying the secant-type method in three different ways and Newton’s interpolatory polynomial of the second degree. The corresponding R-order of convergence is increased from 8 to 4(1+5/2)≈8.472, 9, 10 and 11. The increase of convergence order is attained without any additional function calculations, providing a very high computational efficiency of the proposed methods with memory. Another advantage is a convenient fact that these methods do not use derivatives. Numerical examples and the comparison with existing three-point methods are included to confirm theoretical results and high computational efficiency.
论文关键词:Nonlinear equations,Multipoint methods,Methods with memory,Acceleration of convergence,R-order of convergence,Computational efficiency
论文评审过程:Available online 17 November 2011.
论文官网地址:https://doi.org/10.1016/j.amc.2011.10.057