Abstract
In this paper, we consider an iterative scheme for solving nonlinear ill-posed operator equations of monotone types under minimal and weaker assumptions. The convergence analysis of the scheme is carried out with both a priori and a posteriori parameter choice strategies and the error estimate is derived accordingly. Finally, we supply numerical examples to illustrate the proposed scheme by considering the model of nonlinear integral equations in Wiener-type filtering theory, and the efficiency of the proposed scheme is compared with other schemes.
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References
Andrei D. Polyanin, Alexander V. Manzhirov, Handbook of integral equations, Taylor and Francis (2008).
A. Bakushinskii, A. Goncharskii, Ill-posed Problems: Theory and Applications, Kluwer, Dordrecht (1994).
B. Blaschke, A. Neubauer and O. Scherzer, On convergence rates for the iteratively regularized Gauss-Newton method, IMA J. Numer. Anal., 17 (1997), 421–436.
H. W. Engl, M.Hanke, and A. Neubauer, Regularization of Inverse Problems, Kluwer, Dordrecht (1996).
M. Hanke, A regularization Levenberg Marquardt scheme, with applications to inverse groundwater filtration problems, Inverse Problems, 13(1997), 79–95.
Jin Qi–Nian,On the iteratively regularized Gauss–Newton method for solving nonlinear ill–Posed problems, Mathematics of Computation, 69(232)(2000), 1603–1623.
S. George, On convergence of regularized modified Newton’s method for nonlinear ill-posed problems, J. Inv. Ill-Posed Problems, 18(2010), 133–146.
B. Kaltenbacher, A posteriori choice strategies for some Newton type methods for the regularization of nonlinear ill-posed problems, Numer. Math., 79(1998), 501–528.
P. Mahale and M.T. Nair,Iterated Lavrentiev regularization for non-linear ill-posed problems, ANZIAM J. 51(2009), 191–217.
A. Neubauer, Tikhonov regularization for nonlinear ill-posed problems: optimal convergence rates and finite-dimensional approximation, Inverse Problems 5(1989), 541–553.
D. Pradeep and M.P. Rajan, A regularized iterative scheme for solving nonlinear ill-posed problems, Numerical Functional Analysis and Optimization 37(2016), Issue 3,342-362.
D. Pradeep and M.P. Rajan, A simplified Gauss-Newton iterative scheme for solving nonlinear illposed problems, International Journal of Applied and Computational Mathematics 2(2016), Issue 1, 97–112.
D. Pradeep and M.P. Rajan, An optimal order a posteriori parameter choice strategy with modified Newton iterative scheme for solving nonlinear ill-posed operator equations, International Journal of Computing Science and Mathematics 8(4),342–352.
R. Plato, Iterative and parametric methods for linear ill-posed equations, Habil. Techn. Univ. Berlin, 1995.
N.S. Hoang, Dynamical Systems Method of gradient type for solving nonlinear equations with monotone operators, N.S. Hoang, BIT Numer Math (2010) 50: 751780DOI, 10.1007/s10543-010-0284-2)
N.S. Hoang and A.G. Ramm, Dynamical systems gradient method for solvingnonlinear equations with monotone operators, Acta Applicandae Mathematicae, 106(3)(2009), 473–499.
N.S. Hoang and A.G. Ramm,Dynamical systems method for solving nonlinear equations with monotone operators, Mathematics of Computation, 79(269)(2010), 239–258.
M.P. Rajan, A parameter choice strategy for the regularized approximation of Fredholm integral equations of first kind, International Journal of Computer Mathematics, 87(11), 2612–2622.
M.P. Rajan, On Laverentives regularization for solving Fredholm integral equations of first kind, International Journal of Functional Analysis, Operator Theory and Applications, 1(2), 177-187, 2009.
M.P Rajan, A Modified Convergence Analysis for Solving Fredholm Integral Equations of First Kind, Journal of Integral Equations and Operator Theory, 49, 511-516,2004.
M.P Rajan, Convergence Analysis of a Regularized Approximation For Solving Fredholm Integral Equations of The First Kind, Journal of Mathematical Analysis and Applications 279, 522-530, 2003.
M.P. Rajan and G.D. Reddy, A variant of Tikhonov regularization for parabolic PDE with space derivative multiplied by a small parameter \(\epsilon \), Applied Mathematics and Computation, 259(2015), pp. 412-426.
A.G. Ramm, Random Fields Estimation, World Sci., Singapore (2005)
O. Scherzer, A parameter choice for Tikhonov regularization for solving nonlinear inverse problems leading to optimal rates, Appl. Math.(1993)38, 479–487.
U. Tautenhahn and Qi-nian Jin, Tikhonov regularization and a posteriori rules forsolving nonlinear ill posed problems, Inverse Problems 19(2003), 1–21.
U. Tautenhahn, On the method of Lavrentiev regularization for nonlinear ill-posed problems, Inverse Problems, 18 (2002) 191–207.
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We profoundly thank the unknown referee(s) for their careful reading of the manuscript and valuable suggestions that significantly improved the presentation of the paper as well.
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Communicated by K. Sandeep.
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Pradeep, D., Rajan, M.P. A modified iterative Lavrentiev method for nonlinear monotone ill-posed operators. Indian J Pure Appl Math 55, 341–356 (2024). https://doi.org/10.1007/s13226-023-00368-4
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DOI: https://doi.org/10.1007/s13226-023-00368-4