R. Ramlau and E. Resmerita
Convergence rates for regularization with sparsity constraints.
Submitted for publication.
M. Fornasier, R. Ramlau and G. Teschke.
The application of joint sparsity and total variation minimization algorithms to a real-life art restoration problem.
To appear in Advances in Computational Mathematics.
J. Niebsch and R. Ramlau. Imbalance identification without test masses for wind turbines. J. Solar Energy Engeneering Vol. 131, No. 1, 011010 (2009).
L. Justen and R. Ramlau.
A General Framework for Soft – Shrinkage with Applications to Blind Deconvolution and Wavelet Denoising. Appl. Comp. Harmon. Anal. Vol. 26 No. 1, 43 - 63(2009)
R. Ramlau, G. Teschke, and M. Zhariy
A Compressive Landweber Iteration for Solving Ill-Posed Inverse Problems.
Inverse Problems 24 065013 (2008)
R. Ramlau.
Regularization properties of Tikhonov regularization with sparsity constraints. ETNA, Volume 30, 54-74 (2008)
E.Klann and R.Ramlau.
Regularization by Fractional Filter Methods and Data Smoothing. Inverse Problems 24 No. 2 (April 2008)
J. Niebsch and R. Ramlau.
Balancing wind power plants. ECMI Newsletter (2008).
Gerd Teschke and R.Ramlau. An iterative algorithm for nonlinear inverse problems with joint
sparsity constraints in vector-valued regimes and an application to
color image inpainting. Inverse Problems 23 No 5 (October 2007) 1851-1870.
S. Kindermann and R. Ramlau.
Surrogate functional and tresholding for inverse interface problems Journal for Inverse and Ill - Posed Problems, Volume 15, No. 4, 387 - 402.
R. Ramlau and W. Ring. A Mumford-Shah approach for contour
tomography.
Journal of Computational Physics, Volume 221, Issue 2, 10 February 2007, Pages 539-557.
Shuai Lu, Sergei V Pereverzev and R. Ramlau.
An analysis of Tikhonov regularization for nonlinear ill-posed problems under a general smoothness assumption. Inverse Problems 23 No 1 (February 2007) 217-230.
R. Ramlau.
Tikhonov regularization with non - standard constraints for Tomography.
A. K. Louis, F. Natterer, E. T. Quinto, Mathematical Methods in Tomography, 34/2006, Oberwolfach Report, 62-64, 2006
R. Ramlau and G.
Teschke.
A Tresholding Iteration for Nonlinear Operator Equations with Sparsity Constraints. Numerische Mathematik, Vol. 104, No. 2 (2006), 177 - 203.
E. Klann, P. Maass and R.
Ramlau.
Tikhonov regularization with Wavelet shrinkage for linear inverse
problems. Journal for Inverse and Ill-Posed Problems, Vol. 14, No. 6, 583 - 609, 2006.
J. Niebsch and R. Ramlau
Automatisch Unwuchterkennung am Rotor. Erneuerbare Energien, Ausgabe
5, Mai 2006
R. Ramlau
Auswuchten von rotierenden Systemen. Univationen 02/2006, p. 6
L. Justen and R. Ramlau
A non-iterative regularization approach to blind deconvolution
Inverse Problems, Vol. 22 No 3 (2006), 771-800
R. Ramlau and G. Teschke, Regularization of Sobolev
Embedding Operators and Applications to Medical Imaging and
Meteorological Data.
Part II: Regularization Incorporating Noise with Applications in
Medical Imaging and Meteorological Data. Sampling Theory in Signal and Image Processing, 3(3):2004 R. Ramlau and G. Teschke, Regularization of Sobolev
Embedding Operators and Applications to Medical Imaging and
Meteorological Data.
Part I: Regularization of Sobolev Embedding Operators. Sampling Theory in Signal and Image Processing Volume 3 (2), 2004
F. Stenger and R. Ramlau, Well
posed
Inversion, submitted for publication (2002)
F. Stenger, A.R. Nagsh-Nilshi, J. Niebsch and R. Ramlau, Sampling methods for approximate solution of
pde
In M. Zuhair Nashed and Otmar Scherzer, editors, Inverse Problems,
Image Analysis, and Medical Imaging,
Contemporary Mathematics 313, pages 199-249. American Mathematical
Society , 2002.