In this paper, we investigate an adaptive discretization strategy for ill-posed linear problems combined with a regularization from a class of semiiterative methods. We show that such a discretization approach in combination with a stopping criterion as the discrepancy principle or the balancing principle yields an order optimal regularization scheme and allows to reduce the computational costs.
On adaptive discretization schemes for the solution of ill-posed problems with semiiterative methods
Erb W.
;
2015
Abstract
In this paper, we investigate an adaptive discretization strategy for ill-posed linear problems combined with a regularization from a class of semiiterative methods. We show that such a discretization approach in combination with a stopping criterion as the discrepancy principle or the balancing principle yields an order optimal regularization scheme and allows to reduce the computational costs.
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