Ill-Posed Problems: From Linear to Nonlinear and Beyond
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Date
2021
Publication Type
Book Chapter
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yes
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Abstract
Inverse (ill-posed) problems appear in many applications such as medical imaging, astronomy, seismic imaging, nondestructive testing, signal processing, etc. Typically, these problems cannot be solved by conventional methods as they suffer from instabilities and regularization is required. This chapter has evolved from a mini-course taught at the Summer School on Applied Harmonic Analysis and Machine Learning at the University of Genoa in 2019. It offers an overview of the theory of inverse problems and discusses three ill-posed problems that have been studied rather recently in the literature: limited data reconstruction in computerized tomography, phase retrieval, and image classification with DNNs. The selection highlights that for modern problems, the usefulness of standard theory of regularization can be limited.
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published
Book title
Harmonic and Applied Analysis
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Pages / Article No.
101 - 148
Publisher
Birkhäuser
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09603 - Alaifari, Rima (ehemalig) / Alaifari, Rima (former)