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dc.contributor.authorCho, Taewonen_US
dc.description.abstractIn this age, there are many applications of inverse problems to lots of areas ranging from astronomy, geoscience and so on. For example, image reconstruction and deblurring require the use of methods to solve inverse problems. Since the problems are subject to many factors and noise, we can't simply apply general inversion methods. Furthermore in the problems of interest, the number of unknown variables is huge, and some may depend nonlinearly on the data, such that we must solve nonlinear problems. It is quite different and significantly more challenging to solve nonlinear problems than linear inverse problems, and we need to use more sophisticated methods to solve these kinds of problems.en_US
dc.publisherVirginia Techen_US
dc.rightsAttribution 3.0 United States*
dc.subjectNonlinear Inverse Problemen_US
dc.subjectImage Deblurringen_US
dc.subjectGauss-Newton methoden_US
dc.subjectVariable Projectionen_US
dc.subjectAlternating Optimizationen_US
dc.titleNumerical Methods for Separable Nonlinear Inverse Problems with Constraint and Low Ranken_US
dc.description.degreeMaster of Scienceen_US of Scienceen_US Polytechnic Institute and State Universityen_US
dc.contributor.committeechairChung, Julianneen_US
dc.contributor.committeememberChung, Matthiasen_US
dc.contributor.committeememberEmbree, Marken_US
dc.description.abstractgeneralIn various research areas, there are many required measurements which can't be observed due to physical and economical reasons. Instead, these unknown measurements can be recovered by known measurements. This phenomenon can be modeled and be solved by mathematics.en_US

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Attribution 3.0 United States
License: Attribution 3.0 United States