A third-order Newton-type method to solve systems of nonlinear equations.pdf
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Applied Mathematics and Computation 187 (2007) 630–635
/locate/amcA third-order Newton-type method to solve systems
of nonlinear equations
M.T. Darvishi *, A. Barati
Department of Mathematics, Razi University, Kermanshah 67149, IranAbstract
In this paper, we present a third-order Newton-type method to solve systems of nonlinear equations. In the first we
present theoretical preliminaries of the method. Secondly, we solve some systems of nonlinear equations. All test problems
show the third-order convergence of our method.
2006 Elsevier Inc. All rights reserved.
Keywords: Systems of nonlinear equations; Newton-type method; Third-order convergence1. Introduction
In recent papers [4,5] a new family of third-order convergence methods have been obtained, by using
an integral interpolation of Newton’s method to solve equation f(x) = 0. There has been another approach
based on the Adomian decomposition method on developing iterative method to solve the equation f(x) =
0 (see [3]).
Recently, there has been some progress on Newton-type methods with cubic convergence that do not
require the computation of second derivatives [6]. Chun [2] by improving Newton–Raphson method presented
a new iterative method to solve nonlinear equations. His work is based on modification of the Abbasbandy’s
proposal [1] on improving the order of accuracy of Newton–Raphson method. Frontini and Sormani [4] pre-
sented a third-order iterative method for solving systems of nonlinear equations.
In this paper, we construct a high order iterative method based on Adomian decomposition method to
solve the systems of nonlinear equations. This paper is organized as follows: In the next section we introduce
an iterative method based on Adomian decomposition method to solve f(x) = 0, this method introduced by
Chun [2]. In Section 3 we extend the Chun’s method to solve systems of nonlinear equations. In that section
we state and prove a theorem that shows the cubic convergence of the method. Numerical result
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