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Abstract

This study is about a comprehensive convergence analysis of higher-order Newton-type iterative methods within the framework of Banach spaces. The primary objective is to ascertain locally unique solutions for systems of nonlinear equations. These Newton-type methods are notable for their reliance only on first-order derivative calculations. However, their conventional convergence analysis relies on Taylor expansions, which inherently assume the existence of higher-order derivatives, which are not present on the methods. This dependency limits their practicality. To overcome this limitation, we develop both local and semi-local convergence analysis by imposing hypotheses solely on first-order derivatives that are used by the methods. In the local analysis, our primary focus is to establish convergence domain boundaries while simultaneously estimating error approximations for successive iterates. In the semi-local analysis, we provide sufficient conditions based on arbitrarily chosen initial approximations within a given domain, ensuring the convergence of iterative sequence to a specific solution within that domain. Furthermore, we claim uniqueness of the solution by providing the requisite criteria within the specified domain.Therefore, with these actions, the applicability of these methods is extended in the cases not covered earlier, and under weak conditions. The same technique can be employed to extend the utilization of other methods relying on inverses of linear operators along the same lines. Finally, we validate our theoretical deductions by applying them to real-world problems and presenting the corresponding test results.

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References

  1. Amiri, A.R., Cordero, A., Darvishi, M.T., Torregrosa, J.R.: Preserving the order of convergence: low-complexity Jacobian-free iterative schemes for solving nonlinear systems. J. Comput. Appl. Math. 337, 87–97 (2018)

    Article  MathSciNet  Google Scholar 

  2. Amiri, A., Cordero, A., Darvishi, M.T., Torregrosa, J.R.: A fast algorithm to solve systems of nonlinear equations. J. Comput. Appl. Math. 354, 242–258 (2019)

    Article  MathSciNet  Google Scholar 

  3. Argyros, I.K., Magreñán, Á.A.: Iterative Methods and Their Dynamics with Applications. CRC Press, New York, NY, USA (2017)

    Book  Google Scholar 

  4. Argyros, I.K.: The Theory and Applications of Iteration Methods. CRC Press, New York (2022)

    Google Scholar 

  5. Behl, R., Argyros, I.K.: Local convergence for multi-step high order solvers under weak conditions. Mathematics 8, 179 (2020)

    Article  Google Scholar 

  6. Darvishi, M.T.: Some three-step iterative methods free from second order derivative for finding solutions of systems of nonlinear equations. Int. J. Pure Appl. Math. 57, 557–573 (2009)

    MathSciNet  Google Scholar 

  7. Darvishi, M.T., Barati, A.: A third-order Newtontype method to solve systems of nonlinear equations. Appl. Math. Comput. 187, 630–635 (2007)

    MathSciNet  Google Scholar 

  8. Homeier, H.H.H.: A modified Newton method with cubic convergence. J. Comput. Appl. Math. 169, 161–169 (2004)

    Article  ADS  MathSciNet  Google Scholar 

  9. Homeier, H.H.H.: On Newton-type methods with cubic convergence. J. Comput. Appl. Math. 176, 425–432 (2005)

    Article  ADS  MathSciNet  Google Scholar 

  10. Kumar, D., Kumar, S., Sharma, J.R., Jäntschi, L.: Convergence analysis and dynamical nature of an efficient iterative method in Banach spaces. Mathematics 9, 2510 (2021)

    Article  Google Scholar 

  11. Magreñán, Á.A., Argyros, I.K.: A Contemporary Study of Iterative Methods: Convergence Dynamics and Applications. Academic Press, Elsevier, Amsterdam (2018)

    Google Scholar 

  12. Ortega, J.M., Rheinboldt, W.C.: Iterative Solutions of Nonlinear Equations in Several Variables. Academic Press, New York, USA (1970)

    Google Scholar 

  13. Ostrowski, A.M.: Solution of Equation and Systems of Equations. Academic Press, New York (1960)

    Google Scholar 

  14. Proinov, P.D.: Semi-local Conergence of two iterative methods for simultaneous computation of polynomial zeros. C. R. Acad. Bulgare Sci. 59, 705–712 (2006)

    MathSciNet  Google Scholar 

  15. Rheinboldt, W.C.: An adaptive continuation process for solving systems of nonlinear equations. Banach Center Publ. 3, 129–142 (1978)

    Article  MathSciNet  Google Scholar 

  16. Shakhno, S.M.: Convergence of the two-step combined method and uniqueness of the solution of nonlinear operator equations. J. Comput. Appl. Math. 261, 378–386 (2014)

    Article  MathSciNet  Google Scholar 

  17. Shakhno, S.M.: On an iterative algorithm with superquadratic convergence for solving nonlinear operator equations. J. Comput. Appl. Math. 231, 222–235 (2009)

    Article  ADS  MathSciNet  Google Scholar 

  18. Shakhno, S.M., Gnatyshyn, O.P.: On an iterative algorithm of order 1.839... for solving the nonlinear least squares problems. Appl. Math. Comput. 161, 253–264 (2005)

    MathSciNet  Google Scholar 

  19. Sharma, J.R., Arora, A.: An efficient derivative free numerical methods for solving systems of nonlinear equations. Appl. Anal. Disc. Math. 7, 390–403 (2013)

    Article  Google Scholar 

  20. Sharma, J.R., Guha, R.K., Sharma, R.: An efficient fourth order weighted Newton method for systems of nonlinear equations. Numer. Algor. 62, 307–323 (2013)

    Article  MathSciNet  Google Scholar 

  21. Sharma, J.R., Kumar, S., Argyros, I.K.: Generalized Kung-Traub method and its multi-step iteration in Banach spaces. J. Complex. 54, 101400 (2019)

    Article  MathSciNet  Google Scholar 

  22. Traub, J.F.: Iterative Methods for the Solution of Equations. Chelsea Publishing Company, New York (1982)

    Google Scholar 

  23. Xiao, X.Y., Yin, H.: Achieving higher order of convergence for solving systems of nonlinear equations. Appl. Math. Comput. 311, 251–261 (2017)

    MathSciNet  Google Scholar 

  24. Xiao, X.Y., Yin, H.: Accelerating the convergence speed of iterative methods for solving nonlinear systems. Appl. Math. Comput. 333, 8–19 (2018)

    MathSciNet  Google Scholar 

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Correspondence to Sunil Kumar.

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Kumar, S., Sharma, J.R. & Argyros, I.K. Multi-step methods for equations. Ann Univ Ferrara (2024). https://doi.org/10.1007/s11565-024-00489-6

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  • DOI: https://doi.org/10.1007/s11565-024-00489-6

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