scholarly journals Ball convergence theorems for eighth-order variants of Newton’s method under weak conditions

2015 ◽  
Vol 4 (2) ◽  
pp. 81-90
Author(s):  
Ioannis K. Argyros ◽  
Santhosh George
2019 ◽  
Vol 24 (2) ◽  
pp. 59
Author(s):  
Parimala Sivakumar ◽  
Jayakumar Jayaraman

Three new iterative methods for solving scalar nonlinear equations using weight function technique are presented. The first one is a two-step fifth order method with four function evaluations which is improved from a two-step Newton’s method having same number of function evaluations. By this, the efficiency index of the new method is improved from 1.414 to 1.495. The second one is a three step method with one additional function evaluation producing eighth order accuracy with efficiency index 1.516. The last one is a new fourth order optimal two-step method with efficiency index 1.587. All these three methods are better than Newton’s method and many other equivalent higher order methods. Convergence analyses are established so that these methods have fifth, eighth and fourth order respectively. Numerical examples ascertain that the proposed methods are efficient and demonstrate better performance when compared to some equivalent and optimal methods. Seven application problems are solved to illustrate the efficiency and performance of the proposed methods.


2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Chun-Mei Li ◽  
Shu-Qian Shen

Two new algorithms are proposed to compute the nonsingular square root of a matrixA. Convergence theorems and stability analysis for these new algorithms are given. Numerical results show that these new algorithms are feasible and effective.


2013 ◽  
Vol 6 (10) ◽  
pp. 1794-1798
Author(s):  
Tahir Ahmad ◽  
Norma Alias ◽  
Mahdi Ghanbari ◽  
Mohammad Askaripour

2018 ◽  
Vol 34 (2) ◽  
pp. 135-142
Author(s):  
IOANNIS K. ARGYROS ◽  
◽  
YEOL JE CHO ◽  
SANTHOSH GEORGE ◽  
◽  
...  

The aim of this paper is to extend the applicability of the Gauss-Newton’s method for solving nonlinear least squares problems using our new idea of restricted convergence domains. The new technique uses tighter Lipschitz functions than in earlier papers leading to a tighter ball convergence analysis.


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