Faculty Publications
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Publications by NITK Faculty
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Item A Class of Frozen Regularized Gauss-Newton Methods Under Weak Conditions(Springer, 2025) George, S.; Jidesh, P.Qinian Jin (2010) studied Frozen Regularized Gauss Newton Method (FRGNM) for approximating a solution of nonlinear ill-posed equation. The assumptions used to prove results in Jin’s paper are too restrictive. In this study, we analyze the convergence of FRGNM under weaker assumptions. This way we extend the applicability of FRGNM to the problems which does not satisfy the assumptions in Qinian Jin (2010). We also provide numerical results obtained for five different parameter choice strategies for FRCNM. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.Item A derivative free iterative method for the implementation of Lavrentiev regularization method for ill-posed equations(Kluwer Academic Publishers, 2015) Shubha, V.S.; George, S.; Padikkal, P.In this work, we develop a derivative free iterative method for the implementation of Lavrentiev regularization for approximately solving the nonlinear ill-posed operator equation F(x) = y. Convergence analysis shows that the method converges quadratically. Apart from being totally free of derivatives, the method, under a general source condition provide an optimal order error estimate. We use the adaptive method introduced in Pereverzyev and Schock (SIAM J. Numer. Anal. 43, 2060–2076, 2005) for choosing the regularization parameter. In the concluding section the method is applied to numerical solution of the inverse gravimetry problem. © 2014, Springer Science+Business Media New York.Item Finite dimensional realization of a Tikhonov gradient type-method under weak conditions(Springer-Verlag Italia s.r.l. springer@springer.it, 2016) Shubha, V.S.; George, S.; Padikkal, P.In this paper we consider projection techniques to obtain the finite dimensional realization of a Tikhonov gradient type-method considered in George et al. (Local convergence of a Tikhonov gradient type-method under weak conditions, communicated, 2016) for approximating a solution x^ of the nonlinear ill-posed operator equation F(x) = y. The main advantage of the proposed method is that the inverse of the operator F is not involved in the method. The regularization parameter is chosen according to the adaptive method considered by Pereverzev and Schock (SIAM J Numer Anal 43(5):2060–2076, 2005). We also derive optimal stopping conditions on the number of iterations necessary for obtaining the optimal order of convergence. Using two numerical examples we compare our results with an existing method to justify the theoretical results. © 2016, Springer-Verlag Italia.Item Convergence of a Tikhonov Gradient Type-Method for Nonlinear Ill-Posed Equations(Springer, 2017) George, S.; Shubha, V.S.; Padikkal, P.In this study Tikhonov Gradient type-method is considered for nonlinear ill-posed operator equations. In our convergence analysis, we use hypotheses only on the first Frec?het derivative of F in contrast to the higher order Frec?het derivatives used in the earlier studies. We obtained ‘optimal’ order error estimate by choosing the regularization parameter according to the adaptive method proposed by Pereverzev and Schock (SIAM J Numer Anal 43(5):2060–2076, 2005). © 2017, Springer (India) Private Ltd.