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Modified iterative Runge-Kutta-type methods for nonlinear ill-posed problemsPornsawad, Pornsarp, Böckmann, Christine January 2014 (has links)
This work is devoted to the convergence analysis of a modified Runge-Kutta-type
iterative regularization method for solving nonlinear ill-posed problems under a priori and a posteriori stopping rules. The convergence rate results of the proposed method can be obtained under Hölder-type source-wise condition if the Fréchet derivative is properly scaled and locally Lipschitz continuous. Numerical results are achieved by using the Levenberg-Marquardt and Radau methods.
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Partial Least Squares for Serially Dependent DataSinger, Marco 04 August 2016 (has links)
No description available.
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Generalized Tikhonov regularizationFlemming, Jens 01 November 2011 (has links) (PDF)
The dissertation suggests a generalized version of Tikhonov regularization and analyzes its properties. The focus is on convergence rates theory and an extensive example for regularization with Poisson distributed data is given.
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Quadratic Inverse Problems and Sparsity Promoting RegularizationFlemming, Jens 16 January 2018 (has links) (PDF)
Ill-posed inverse problems with quadratic structure are introduced, studied and solved. As an example an inverse problem appearing in laser optics is solved numerically based on a new regularized inversion algorithm. In addition, the theory of sparsity promoting regularization is extended to situations in which sparsity cannot be expected and also to equations with non-injective operators.
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Generalized Tikhonov regularization: Basic theory and comprehensive results on convergence ratesFlemming, Jens 27 October 2011 (has links)
The dissertation suggests a generalized version of Tikhonov regularization and analyzes its properties. The focus is on convergence rates theory and an extensive example for regularization with Poisson distributed data is given.
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Quadratic Inverse Problems and Sparsity Promoting Regularization: Two subjects, some links between them, and an application in laser opticsFlemming, Jens 11 January 2018 (has links)
Ill-posed inverse problems with quadratic structure are introduced, studied and solved. As an example an inverse problem appearing in laser optics is solved numerically based on a new regularized inversion algorithm. In addition, the theory of sparsity promoting regularization is extended to situations in which sparsity cannot be expected and also to equations with non-injective operators.
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