The SFB program expired on September 30, 2008. For the link to the successor project click DK Computational Mathematics
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Publications of the Project F1308


Article - 2005


September 27, 2008

Bibliography

1
M. Burger and M. Hintermueller.
Projected gradient flows for bv / level set relaxation.
PAMM, 5:11-14, 2005.
2
M. Burger and A. Hofinger.
Regularized greedy algorithms for network training with data noise.
Computing, 74(1):1-22, 2005.
3
M. Burger and S. Osher.
A survey on level set methods for inverse problems and optimal design.
European J. Appl. Math., 16(2):263-301, 2005.
4
H. Egger and H. W. Engl.
Tikhonov regularization applied to the inverse problem of option pricing: Convergence analysis and rates.
Inverse Problems, 21:1027-1045, 2005.
5
H. Egger, H. W. Engl, and M. V. Klibanov.
Global uniqueness and Hölder stability for recovering a nonlinear source term in a parabolic equation.
Inverse Problems, 21:271-290, 2005.
6
H. Egger and A. Neubauer.
Preconditioning Landweber iteration in Hilbert scales.
Numerische Mathematik, 101:643-662, 2005.
7
H. Engl, P. Fusek, and S. Pereverzev.
Natural linearization for the identification of nonlinear heat transfer laws.
Journal of Inv. and Ill-Posed Problems, 13:567-582, 2005.
8
H. W. Engl, A. Hofinger, and S. Kindermann.
Convergence rates in the Prokhorov metric for assessing uncertainty in ill-posed problems.
Inverse Problems, 21:399-412, 2005.
9
L. He, S. Osher, and M. Burger.
Iterative total variation regularization with non-quadratic fidelity.
J. Math. Imag. Vision, 26:167-184, 2005.
10
P. Kügler.
Convergence rate analysis of a derivative free landweber iteration for parameter identification in certain elliptic pdes.
Numer. Math., 101(1):165-184, 2005.
11
S. Osher, M. Burger, D. Goldfarb, J. Xu, and W. Yin.
An iterative regularization method for total variation based image restoration.
Multiscale Modelling and Simulation, 4:460-489, 2005.




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SpezialForschungsBereich SFB F013 | Special Research Program of the FWF - Austrian Science Fund