The discrepancy principle for Tikhonov regularization in Banach spaces - Anzengruber, Stephan W.
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This book is about inverse problems. A classical example of such an inverse problem is computerized tomography (CT), where one attempts to recover an image of, say, the human brain from measured x-ray intensities. Such measurements will in general be noisy, but even very little noise can have a severe impact on the quality of the reconstructed images. To overcome these difficulties regularization methods have been developed, which stabilize the reconstruction process. We study here one such method, known as Tikhonov-regularization, and prove general regularizing properties as well as rates on the speed of the convergence.…mehr

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Produktbeschreibung
This book is about inverse problems. A classical example of such an inverse problem is computerized tomography (CT), where one attempts to recover an image of, say, the human brain from measured x-ray intensities. Such measurements will in general be noisy, but even very little noise can have a severe impact on the quality of the reconstructed images. To overcome these difficulties regularization methods have been developed, which stabilize the reconstruction process. We study here one such method, known as Tikhonov-regularization, and prove general regularizing properties as well as rates on the speed of the convergence.
Autorenporträt
... studied 'Technical Mathematics' at the Johannes Kepler University in Linz, Austria, where he graduated with distinction in 2007. He conducted the research leading to the present PhD thesis at the 'Johann Radon Institute for Computational and Applied Mathematics' (RICAM).