Iterative regularization for elliptic inverse problems
Elliptic inverse problems can be formulated using coefficient-dependent energy least-squares functionals, resulting in a smooth, convex objective functional. A variational inequality emerges as a necessary and sufficient optimality condition. The principle of iterative regularization, when coupled with the auxiliary problem principle, results in a strongly convergent scheme for the solution of elliptic inverse problems.
regularization inverse problem variational inequality auxiliary problem principle parameter identification iterative methods