This paper concerns the A smooth regularization method for linear ill posed equations in the presence of perturbed operators and noisy data. The semi and full a posteriori Morozov discrepancy principles for...This paper concerns the A smooth regularization method for linear ill posed equations in the presence of perturbed operators and noisy data. The semi and full a posteriori Morozov discrepancy principles for choosing the regularization parameter are proposed, which lead to satisfactory results.展开更多
This article presents a fast convergent method of iterated regularization based on the idea of Landweber iterated regularization, and a method for a-posteriori choice by the Morozov discrepancy principle and the optim...This article presents a fast convergent method of iterated regularization based on the idea of Landweber iterated regularization, and a method for a-posteriori choice by the Morozov discrepancy principle and the optimum asymptotic convergence order of the regularized solution is obtained. Numerical test shows that the method of iterated regularization can quicken the convergence speed and reduce the calculation burden efficiently.展开更多
文摘This paper concerns the A smooth regularization method for linear ill posed equations in the presence of perturbed operators and noisy data. The semi and full a posteriori Morozov discrepancy principles for choosing the regularization parameter are proposed, which lead to satisfactory results.
文摘This article presents a fast convergent method of iterated regularization based on the idea of Landweber iterated regularization, and a method for a-posteriori choice by the Morozov discrepancy principle and the optimum asymptotic convergence order of the regularized solution is obtained. Numerical test shows that the method of iterated regularization can quicken the convergence speed and reduce the calculation burden efficiently.
