Article
Licensed
Unlicensed
Requires Authentication
Solving constraint ill-posed problems using Ginzburg–Landau regularization functionals
-
F. Frühauf
Published/Copyright:
March 5, 2008
We consider constrained ill-posed operator equations. The constraints are such that in one case we restrict the domain to functions which are piecewise constant. In another case we allow only functions that attain values in a certain interval. We use Ginzburg–Landau regularization methods for solving these equations. In our numerical examples we consider the inverse conductivity problem which has applications in electrical impedance tomography. We present a numerical implementation along with some results and compare them with modified H1-Tikhonov regularization methods.
Received: 2006-June-06
Published Online: 2008-03-05
Published in Print: 2008-01
© de Gruyter
You are currently not able to access this content.
You are currently not able to access this content.
Articles in the same Issue
- Inverse electromagnetic scattering by a perfect conductor in a chiral environment
- Recovering a potential from Cauchy data in the two-dimensional case
- Solving constraint ill-posed problems using Ginzburg–Landau regularization functionals
- An inverse problem of identifying source coefficient in solute transportation
- Boundary integral equations for acoustical inverse sound-soft scattering
- A note on logarithmic convergence rates for nonlinear Tikhonov regularization
- Analytic approximation with real constraints, with applications to inverse diffusion problems
Articles in the same Issue
- Inverse electromagnetic scattering by a perfect conductor in a chiral environment
- Recovering a potential from Cauchy data in the two-dimensional case
- Solving constraint ill-posed problems using Ginzburg–Landau regularization functionals
- An inverse problem of identifying source coefficient in solute transportation
- Boundary integral equations for acoustical inverse sound-soft scattering
- A note on logarithmic convergence rates for nonlinear Tikhonov regularization
- Analytic approximation with real constraints, with applications to inverse diffusion problems
