Optimal Newton–Secant like methods without memory for solving nonlinear equations with its dynamics
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
We construct two optimal Newton–Secant like iterative methods for solving nonlinear equations. The proposed classes have convergence order four and eight and cost only three and four function evaluations per iteration, respectively. These methods support the Kung and Traub conjecture and possess a high computational efficiency. The new methods are illustrated by numerical experiments and a comparison with some existing optimal methods. We conclude with an investigation of the basins of attraction of the solutions in the complex plane.
Details
Original language | English |
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Pages (from-to) | 1759-1777 |
Number of pages | 19 |
Journal | International Journal of Computer Mathematics |
Volume | 94 |
Issue number | 9 |
Publication status | Published - 2 Sept 2017 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0003-0967-6747/work/149795406 |
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Keywords
ASJC Scopus subject areas
Keywords
- Kung and Traub's conjecture, Multi-point iterative methods, Newton–Secant method