9 research outputs found

    Directional k-Step Newton Methods in n Variables and its Semilocal Convergence Analysis

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    [EN] The directional k-step Newton methods (k a positive integer) is developed for solving a single nonlinear equation in n variables. Its semilocal convergence analysis is established by using two different approaches (recurrent relations and recurrent functions) under the assumption that the first derivative satisfies a combination of the Lipschitz and the center-Lipschitz continuity conditions instead of only Lipschitz condition. The convergence theorems for the existence and uniqueness of the solution for each of them are established. Numerical examples including nonlinear Hammerstein-type integral equations are worked out and significantly improved results are obtained. It is shown that the second approach based on recurrent functions solves problems failed to be solved by first one using recurrent relations. This demonstrates the efficacy and applicability of these approaches. This work extends the directional one and two-step Newton methods for solving a single nonlinear equation in n variables. Their semilocal convergence analysis using majorizing sequences are studied in Levin (Math Comput 71(237): 251-262, 2002) and Ioannis (Num Algorithms 55(4): 503-528, 2010) under the assumption that the first derivative satisfies the Lipschitz and the combination of the Lipschitz and the center-Lipschitz continuity conditions, respectively. Finally, the computational order of convergence and the computational efficiency of developed method are studied.The authors thank the referees for their fruitful suggestions which have uncovered several weaknesses leading to the improvement in the paper. A. Kumar wishes to thank UGC-CSIR(Grant no. 2061441001), New Delhi and IIT Kharagpur, India, for their financial assistance during this work.Kumar, A.; Gupta, D.; Martínez Molada, E.; Singh, S. (2018). Directional k-Step Newton Methods in n Variables and its Semilocal Convergence Analysis. Mediterranean Journal of Mathematics. 15(2):15-34. https://doi.org/10.1007/s00009-018-1077-0S1534152Levin, Y., Ben-Israel, A.: Directional Newton methods in n variables. Math. Comput. 71(237), 251–262 (2002)Argyros, I.K., Hilout, S.: A convergence analysis for directional two-step Newton methods. Num. Algorithms 55(4), 503–528 (2010)Lukács, G.: The generalized inverse matrix and the surface-surface intersection problem. In: Theory and Practice of Geometric Modeling, pp. 167–185. Springer (1989)Argyros, I.K., Magreñán, Á.A.: Extending the applicability of Gauss–Newton method for convex composite optimization on Riemannian manifolds. Appl. Math. Comput. 249, 453–467 (2014)Argyros, I.K.: A semilocal convergence analysis for directional Newton methods. Math. Comput. 80(273), 327–343 (2011)Ortega, J.M., Rheinboldt, W.C.: Iterative solution of nonlinear equations in several variables. SIAM (2000)Argyros, I.K., Hilout, S.: Weaker conditions for the convergence of Newton’s method. J. Complex. 28(3), 364–387 (2012)Argyros, I.K., Hilout, S.: On an improved convergence analysis of Newton’s method. Appl. Math. Comput. 225, 372–386 (2013)Tapia, R.A.: The Kantorovich theorem for Newton’s method. Am. Math. Mon. 78(4), 389–392 (1971)Argyros, I.K., George, S.: Local convergence for some high convergence order Newton-like methods with frozen derivatives. SeMA J. 70(1), 47–59 (2015)Martínez, E., Singh, S., Hueso, J.L., Gupta, D.K.: Enlarging the convergence domain in local convergence studies for iterative methods in Banach spaces. Appl. Math. Comput. 281, 252–265 (2016)Argyros, I.K., Behl, R. Motsa,S.S.: Ball convergence for a family of quadrature-based methods for solving equations in banach Space. Int. J. Comput. Methods, pp. 1750017 (2016)Parhi, S.K., Gupta, D.K.: Convergence of Stirling’s method under weak differentiability condition. Math. Methods Appl. Sci. 34(2), 168–175 (2011)Prashanth, M., Gupta, D.K.: A continuation method and its convergence for solving nonlinear equations in Banach spaces. Int. J. Comput. Methods 10(04), 1350021 (2013)Parida, P.K., Gupta, D.K.: Recurrence relations for semilocal convergence of a Newton-like method in banach spaces. J. Math. Anal. Appl. 345(1), 350–361 (2008)Argyros, I.K., Hilout, S.: Convergence of Directional Methods under mild differentiability and applications. Appl. Math. Comput. 217(21), 8731–8746 (2011)Amat, S, Bermúdez, C., Hernández-Verón, M.A., Martínez, E.: On an efficient k-step iterative method for nonlinear equations. J. Comput. Appl. Math. 302, 258–271 (2016)Hernández-Verón, M.A., Martínez, E., Teruel, C.: Semilocal convergence of a k-step iterative process and its application for solving a special kind of conservative problems. Num. Algorithms, pp. 1–23Argyros, M., Hernández, I.K., Hilout, S., Romero, N.: Directional Chebyshev-type methods for solving equations. Math. Comput. 84(292), 815–830 (2015)Davis, P.J., Rabinowitz, P.: Methods of numerical integration. Courier Corporation (2007)Cordero, A, Torregrosa, J.R.: Variants of Newton’s method using fifth-order quadrature formulas. Appl. Math. Computation . 190(1), 686–698 (2007)Weerakoon, S., Fernando, T.G.I.: A variant of Newton’s method with accelerated third-order convergence. Appl. Math. Lett. 13(8), 87–93 (2000

    A Two-step Quaternionic Root-finding Method

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    In this paper we present a new method for determining simultaneously all the simple roots of a quaternionic polynomial. The proposed algorithm is a two-step iterative Weierstrass-like method and has cubic order of convergence. We also illustrate a variation of the method which combines the new scheme with a recently proposed deflation procedure for the case of polynomials with spherical roots.FCT -Fundação para a Ciência e a Tecnologia(UIDB/00013/2020

    Optimal control of system governed by nonlinear volterra integral and fractional derivative equations

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    AbstractThis work presents a novel formulation for the numerical solution of optimal control problems related to nonlinear Volterra fractional integral equations systems. A spectral approach is implemented based on the new polynomials known as Chelyshkov polynomials. First, the properties of these polynomials are studied to solve the aforementioned problems. The operational matrices and the Galerkin method are used to discretize the continuous optimal control problems. Thereafter, some necessary conditions are defined according to which the optimal solutions of discrete problems converge to the optimal solution of the continuous ones. The applicability of the proposed approach has been illustrated through several examples. In addition, a comparison is made with other methods for showing the accuracy of the proposed one, resulting also in an improved efficiency

    An efficient hybrid pseudo-spectral method for solving optimal control of Volterra integral systems

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    In this paper, a new pseudo-spectral (PS) method is developed for solving optimal controproblems governed by the non-linear Volterra integral equation(VIE). The novel method is based upon approximating the state and control variables by the hybrid of block pulse functions and Legendre polynomials. The properties of hybrid functions are presented. The numerical integration and collocation method is utilized to discretize the continuous optimal control problem and then the resulting large-scale finite-dimensional non-linear programming (NLP) is solved by the existing well-developed algorithm in Mathematica software. A set of sufficient conditions is presented under which optimal solutions of discrete optimal control problems converge to the optimal solution of the continuous problem. The error bound of approximation is also given. Numerical experiments confirm efficiency of the proposed method especially for problems with non-sufficiently smooth solutions belonging to class C1C^1 or C2C^2

    A Comparative Study of Iterative Riemann Solvers for the Shallow Water and Euler Equations

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    The Riemann problem for first-order hyperbolic systems of partial differential equations is of fundamental importance for both theoretical and numerical purposes. Many approximate solvers have been developed for such systems; exact solution algorithms have received less attention because computation of the exact solution typically requires iterative solution of algebraic equations. Iterative algorithms may be less computationally efficient or might fail to converge in some cases. We investigate the achievable efficiency of robust iterative Riemann solvers for relatively simple systems, focusing on the shallow water and Euler equations. We consider a range of initial guesses and iterative schemes applied to an ensemble of test Riemann problems. For the shallow water equations, we find that Newton's method with a simple modification converges quickly and reliably. For the Euler equations we obtain similar results; however, when the required precision is high, a combination of Ostrowski and Newton iterations converges faster. These solvers are slower than standard approximate solvers like Roe and HLLE, but come within a factor of two in speed. We also provide a preliminary comparison of the accuracy of a finite volume discretization using an exact solver versus standard approximate solvers

    Two-step Newton methods

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    We present sufficient convergence conditions for two-step Newton methods in order to approximate a locally unique solution of a nonlinear equation in a Banach space setting. The advantages of our approach over other studies such as Argyros et al. (2010) [5], Chen et al. (2010) [11], Ezquerro et al. (2000) [16], Ezquerro et al. (2009) [15], Hernández and Romero (2005) [18], Kantorovich and Akilov (1982) [19], Parida and Gupta (2007) [21], Potra (1982) [23], Proinov (2010) [25], Traub (1964) [26] for the semilocal convergence case are: weaker sufficient convergence conditions, more precise error bounds on the distances involved and at least as precise information on the location of the solution. In the local convergence case more precise error estimates are presented. These advantages are obtained under the same computational cost as in the earlier stated studies. Numerical examples involving Hammerstein nonlinear integral equations where the older convergence conditions are not satisfied but the new conditions are satisfied are also presented in this study for the semilocal convergence case. In the local case, numerical examples and a larger convergence ball are obtained. © 2013 Elsevier Inc. All rights reserved

    Two-step Newton methods

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    Capítulo del libro "Contemporary study of iterative methods: convergence, dynamics and applications"In this chapter we extend the applicability of two-step Newton's method for solving nonlinear equations

    Two-step Newton Methods and Their Applications

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