In this paper, we deal with nonlinear ill-posed problems involving m-accretive mappings in Banach spaces. We consider a derivative and inverse free method for the imple- mentation of Lavrentiev regularization method. ...In this paper, we deal with nonlinear ill-posed problems involving m-accretive mappings in Banach spaces. We consider a derivative and inverse free method for the imple- mentation of Lavrentiev regularization method. Using general HSlder 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.展开更多
In this paper, a simplified iterative regnlarization method was used to solve the operator equations of the first kind involving semi-positive definite operators, the convergence rates of regularized solutions were ob...In this paper, a simplified iterative regnlarization method was used to solve the operator equations of the first kind involving semi-positive definite operators, the convergence rates of regularized solutions were obtained and a posteriori parametr choice strategy was given.展开更多
We propose a multiscale projection method for the numerical solution of the irtatively regularized Gauss-Newton method of nonlinear integral equations.An a posteriori rule is suggested to choose the stopping index of ...We propose a multiscale projection method for the numerical solution of the irtatively regularized Gauss-Newton method of nonlinear integral equations.An a posteriori rule is suggested to choose the stopping index of iteration and the rates of convergence are also derived under the Lipschitz condition.Numerical results are presented to demonstrate the efficiency and accuracy of the proposed method.展开更多
基金National Institute of Technology Karnataka, India, for the financial support
文摘In this paper, we deal with nonlinear ill-posed problems involving m-accretive mappings in Banach spaces. We consider a derivative and inverse free method for the imple- mentation of Lavrentiev regularization method. Using general HSlder 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.
文摘In this paper, a simplified iterative regnlarization method was used to solve the operator equations of the first kind involving semi-positive definite operators, the convergence rates of regularized solutions were obtained and a posteriori parametr choice strategy was given.
基金Supported in part by the Natural Science Foundation of China under grants 11761010 and 61863001.
文摘We propose a multiscale projection method for the numerical solution of the irtatively regularized Gauss-Newton method of nonlinear integral equations.An a posteriori rule is suggested to choose the stopping index of iteration and the rates of convergence are also derived under the Lipschitz condition.Numerical results are presented to demonstrate the efficiency and accuracy of the proposed method.
