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Please use this identifier to cite or link to this item: http://hdl.handle.net/1813/5583
Title: Piecewise Differentiable Minimization for Ill-posed Inverse Problems
Authors: Li, Yuying
Keywords: theory center
Issue Date: Aug-1996
Publisher: Cornell University
Citation: http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.tc/96-252
Abstract: Based on minimizing a piece wise differentiable lp function subject to a single inequality constraint, this paper discusses algorithms for a discretized regularization problem for ill-posed inverse problems. We examine computational challenges of solving this regularization problem. Possible minimization algorithms such as the steepest descent method, iteratively weighted least squares (IRLS) method and a recent globally convergent affine scaling Newton approach are considered. Limitations and efficiency of these algorithms are demonstrated using the geophysical travel time tomographic inversion and image restoration applications.
URI: http://hdl.handle.net/1813/5583
Appears in Collections:Cornell Theory Center Technical Reports

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