It is shown that Tikhonov regularization for ill- posed operator equation \(Kx = y\) using a possibly unbounded regularizing operator \(L\) yields an orderoptimal algorithm with respect to certain stability set when the regularization parameter is chosen according to the Morozov's discrepancy principle. A more realistic error estimate is derived when the operators \(K\) and \(L\) are related to a Hilbert scale in a suitable manner. The result includes known error estimates for ordininary Tikhonov regularization and also the estimates available under the Hilbert scale approach
A convergence rate is established for nonstationary iterated Tikhonov regularization, applied to ill...
Se establecen órdenes de convergencia débil para las soluciones aproximadas obtenidas por el método ...
Choosing the regularization parameter for an ill-posed problem is an art based on good heuristics an...
A class of regularization methods using unbounded regularizing operators is considered for obtaining...
We study the application of Tikhonov regularization to ill-posed nonlinear operator equations. The o...
We are concerned with a parameter choice strategy for the Tikhonov regularization \((\tilde{A}+\alph...
AbstractWe describe here a stable algorithm for the solution of an operator equation in a Hilbert sp...
AbstractIn this paper we derive conditions under which the constrained Tikhonov-regularized solution...
We construct with the aid of regularizing filters a new class of improved regularization methods, ca...
We construct with the aid of regularizing filters a new class of improved regularization methods, ca...
When deriving rates of convergence for the approximations generated by the application of Tikhonov r...
In the present paper for a stable solution of severely ill-posed problems with perturbed input data,...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
For Tikhonov regularization of ill-posed nonlinear operator equations, convergence is studied in a H...
For solving linear ill-posed problems with noisy data, regularization methods are required. In this ...
A convergence rate is established for nonstationary iterated Tikhonov regularization, applied to ill...
Se establecen órdenes de convergencia débil para las soluciones aproximadas obtenidas por el método ...
Choosing the regularization parameter for an ill-posed problem is an art based on good heuristics an...
A class of regularization methods using unbounded regularizing operators is considered for obtaining...
We study the application of Tikhonov regularization to ill-posed nonlinear operator equations. The o...
We are concerned with a parameter choice strategy for the Tikhonov regularization \((\tilde{A}+\alph...
AbstractWe describe here a stable algorithm for the solution of an operator equation in a Hilbert sp...
AbstractIn this paper we derive conditions under which the constrained Tikhonov-regularized solution...
We construct with the aid of regularizing filters a new class of improved regularization methods, ca...
We construct with the aid of regularizing filters a new class of improved regularization methods, ca...
When deriving rates of convergence for the approximations generated by the application of Tikhonov r...
In the present paper for a stable solution of severely ill-posed problems with perturbed input data,...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
For Tikhonov regularization of ill-posed nonlinear operator equations, convergence is studied in a H...
For solving linear ill-posed problems with noisy data, regularization methods are required. In this ...
A convergence rate is established for nonstationary iterated Tikhonov regularization, applied to ill...
Se establecen órdenes de convergencia débil para las soluciones aproximadas obtenidas por el método ...
Choosing the regularization parameter for an ill-posed problem is an art based on good heuristics an...