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Derivative free regularization method for nonlinear ill-posed equations in Hilbert scales
(De Gruyter Open Ltd, 2019) George, S.; Kanagaraj, K.
In this paper, we deal with nonlinear ill-posed operator equations involving a monotone operator in the setting of Hilbert scales. Our convergence analysis of the proposed derivative-free method is based on the simple property of the norm of a self-adjoint operator. Using a general Hölder-type source condition, we obtain an optimal order error estimate. Also we consider the adaptive parameter choice strategy proposed by Pereverzev and Schock (2005) for choosing the regularization parameter. Finally, we applied the proposed method to the parameter identification problem in an elliptic PDE in the setting of Hilbert scales and compare the results with the corresponding method in Hilbert space. © 2019 De Gruyter. All rights reserved.
Discrepancy principles for fractional Tikhonov regularization method leading to optimal convergence rates
(Springer, 2020) Kanagaraj, K.; Reddy, G.D.; George, S.
Fractional Tikhonov regularization (FTR) method was studied in the last few years for approximately solving ill-posed problems. In this study we consider the Schock-type discrepancy principle for choosing the regularization parameter in FTR and obtained the order optimal convergence rate. Numerical examples are provided in this study. © 2019, Korean Society for Informatics and Computational Applied Mathematics.