A new family of Newton-type iterative methods with and without memory for solving nonlinear equations
A new family of two-step iterative methods for solving nonlinear equations is obtained. The order of convergence of the new family without memory is four requiring three functional evaluations, which implies that this family is optimal according to \textit{H. T. Kung} and \textit{J. F. Traub}'s conjecture [J. Assoc. Comput. Mach. 21, 643--651 (1974; Zbl 0289.65023)]. Further accelerations of the convergence speed are obtained by varying a free parameter in per full iteration. This self-accelerating parameter is calculated by using information available from the current and previous iteration. The corresponding \(R\)-order of convergence is increased. The increase of the convergence order is attained without any additional calculations so that the family of the methods with memory possesses a very high computational efficiency. Another advantage of the new methods is that they remove the severe condition \(f'(x)\) in a neighborhood of the required root imposed on Newton's method. Numerical comparisons are made to show the performance of the new methods.
scientific article; zbMATH DE number 6418664