On developing an optimal Jarratt-like class for solving nonlinear equations

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Forum-Editrice Universitaria Udinese SRL

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info:eu-repo/semantics/openAccess

Özet

It is attempted to derive an optimal class of methods without memory from Ozban’s method [A. Y. Ozban, Some New Variants of Newton’s Method, Appl. Math. Lett. 17 (2004) 677-682]. To this end, we try to introduce a weight function in the second step of the method and to find some suitable conditions, so that the modified method is optimal in the sense of Kung and Traub’s conjecture. Also, convergence analysis along with numerical implementations are included to verify both theoretical and practical aspects of the proposed optimal class of methods without memory. © 2020 Forum-Editrice Universitaria Udinese SRL. All rights reserved.

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Convergence analysis, Iterative method, Kung and Traub’s conjecture, Nonlinear equations, Optimal method

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Italian Journal of Pure and Applied Mathematics

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43

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Attary, M., & Agarwal, P. (2020). On developing an optimal Jarratt-like class for solving nonlinear equations. Ital. J. Pure Appl. Math, 43, 523-530.

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