SpezialForschungsBereich SFB F013: Publication Lists

Publications of the Project F1308

TechRepMisc

September 27, 2008

Bibliography

1: J. Baumeister and A. Leitao.
Optimal exploitation of renewable resource stocks: Necessary conditions.
SFB-Report 00-36, SFB F013, J. Kepler University Linz, University Linz, 2001.
2: H. Benameur, M. Burger, and B. Hackl.
Level set methods for inverse problems in linear elasticity.
SFB-Report 2003-12, University Linz, 2003.
3: H. Benameur, M. Burger, and B. Hackl.
On some inverse problems in linear elasticity.
CAM-Report 03-55, UCLA, 2003.
4: M. Burger.
Growth fronts of first-order Hamilton-Jacobi equations.
SFB Report 02-8, University Linz, 2002.
5: M. Burger.
Numerical simulation of anisotropic surface diffusion with curvature-dependent energy.
CAM-Report 04-06, Department of Mathematics, UCLA, 2003.
6: M. Burger.
Weak solutions for the mean curvature flow of planar graphs.
SFB-Report 03-01, SFB F 013, University Linz, 2003.
7: M. Burger, V. Capasso, and D. Morale.
On an aggregation model with long and short range interactions.
CAM-Report 03-30, Department of Mathematics, UCLA, 2003.
8: M. Burger, B. Hackl, and W. Ring.
Incorporating topological derivatives into level set methods.
CAM-Report 03-46, UCLA, 2003.
9: M. Burger, J. Haslinger, and U. Bodenhofer.
Regularized optimization of fuzzy controllers.
Sfb-report 01-9, SFB F 013, University of Linz, 2001.
10: M. Burger and A. Hofinger.
Regularized greedy algorithms for neural network training with data noise.
03-04, Johannes Kepler University Linz, Spezialforschungsbereich SFB013, April 2003.
11: M. Burger and W. Mühlhuber.
Iterative regularization of parameter identification problems by SQP methods.
SFB Report 01-18, SFB F013, University Linz, 2001.
12: M. Burger and W. Mühlhuber.
Numerical approximation of an SQP-type method for parameter identification.
SFB Report 01-19, SFB F013, University Linz, 2001.
13: M. Burger and S. Osher.
Convergence rates of convex variational regularization.
CAM-Report 04-10, Department of Mathematics, UCLA, 2003.
14: M. Burger and S. Osher.
A survey on level set methods for inverse problems and optimal design.
CAM-Report 04-02, Department of Mathematics, UCLA, 2003.
15: M. Burger, E. Resmerita, and L. He.
Error estimation for Bregman iteration and inverse scale space methods.
CAM-Report 07-1, UCLA, 2007.
16: M. Burger and R. Stainko.
Phase-field relaxation of topology optimization with local stress constraints.
Technical Report 2004-35, J. Kepler University Linz, SFB F013, 2004.
17: R. Celorrio and A. Hofinger.
A real-time solution for an inverse Cauchy problem in cardiology.
Technical report, SFB F013, 2005.
18: H. Egger.
Accelerated Newton-Landweber iterations for regularizing nonlinear inverse problems.
SFB-Report 2005-03, SFB F013, 2005.
19: H. Egger.
Preconditioning cgne-iterations for inverse problems.
Report 2006-9, SFB013, March 2006.
20: H. Egger.
Y-scale regularization.
Report 2006-7, SFB013, March 2006.
21: H. W. Engl, A. Hofinger, and S. Kindermann.
Convergence rates in the Prokhorov metric for assessing uncertainty in ill-posed problems.
Technical report, SFB F013, September 2004.
22: H. W. Engl and P. Kügler.
The Influence of the Equation Type on Iterative Parameter Identification Problems which are Elliptic or Hyperbolic in the Parameter.
SFB-Report 01-25, SFB F013, University of Linz, July 2001.
23: H. W. Engl and A. Leitao.
A Mann iterative method for elliptic Cauchy problems.
Technical Report 00-38, SFB F013, J. Kepler University Linz, 2000.
24: H. Gu and M. Burger.
Numerical-symbolic methods for parameter-dependent geometric differential equations.
SFB-Report 05-01, University Linz, 2005.
25: B. Hackl.
Methods for reliable topology changes for perimeter regularized geometric inverse problems.
Technical Report SFB 2006-3, RICAM & SFB F013, 2006.
26: A. Hofinger.
Nonlinear function approximation: Computing smooth solutions with an adaptive greedy algorithm.
Technical report, SFB F013, September 2004.
27: A. Hofinger.
Assessing uncertainty in linear inverse problems with the metrics of Ky Fan and Prokhorov.
SFB-Report 2006-23, SFB F013, 2006.
28: A. Hofinger.
The metrics of Prokhorov and Ky Fan for assessing uncertainty in inverse problems.
SFB-Report 2006-20, SFB F013, 2007.
29: A. Hofinger and S. Kindermann.
Assessing uncertainty in nonlinear inverse problems with the metrics of Ky Fan and Prokhorov.
SFB-Report 2006-31, SFB F013, 2006.
30: A. Hofinger and H. K. Pikkarainen.
Convergence rates for the bayesian approach to linear inverse problems.
Technical Report 2006-32, SFB F013, November 2006.
31: A. Hofinger and H. K. Pikkarainen.
Convergence rates for linear inverse problems in the presence of an additive normal noise.
Technical Report 2007-3, SFB F013, January 2007.
32: A. Hofinger and F. Pillichshammer.
Learning a function from noisy samples at a finite sparse set of points.
Technical report, SFB F013, 2005.
33: T. Hohage.
ITREG, 1998.
C++ code for iterative regularization methods for nonlinear ill-posed problems, e.g., inverse scattering, inverse potential, and parameter identification problems in PDEs.
34: T. Hohage.
On the numerical solution of a 3D inverse medium scattering problem.
Sfb report, SFB013-Report No.00-27, 2000.
35: J. M. J. Huttunen and H. K. Pikkarainen.
Discretization error in dynamical inverse problems: one-dimensional model case.
Technical Report 2006-22, RICAM, July 2006.
36: B. Kaltenbacher.
On a multigrid method for ill-posed problems.
Technical report, SFB013-report No.99-20, 1999.
37: B. Kaltenbacher.
V-cycle convergence of some multigrid methods for ill-posed problems.
Technical Report 00-29, SFB013, 2000.
38: B. Kaltenbacher and H. Benameur.
Regularization of parameter estimation by adaptive discretization using refinement and coarsening indicators.
SFB-Report 01-29, SFB F013, University of Linz, September 2001.
39: B. Kaltenbacher and M. Kaltenbacher.
Identification of piezoelectric material parameters.
Technical Report 2000-32, SFB F013, 2000.
40: B. Kaltenbacher, M. Kaltenbacher, and S. Reitzinger.
Identification of nonlinear B-H curves based on magnetic field computations and multigrid methods for ill-posed problems.
SFB-Report 01-17, SFB F013, University of Linz, May 2001.
41: B. Kaltenbacher and J. Schöberl.
A saddle point variational formulation for projection-regularized parameter identification.
Technical Report 00-13, SFB Report, 2000.
42: P. Kügler.
An approach to online parameter estimation in nonlinear dynamical systems.
SFB Report 2004-18, Johannes Kepler University Linz, 2004.
43: H. K. Pikkarainen.
State estimation approach to nonstationary inverse problems: discretization error and filtering problem.
Technical Report 2005-20, RICAM, October 2005.

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