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(2019.10.24)Associate Prof. Ye Zhang:Two new non-negativity preserving iterative regularization methods for solving inverse problems
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Update time: 2019-11-06
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Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:

Associate Prof. Ye Zhang, Shenzhen MSU-BIT University

Inviter:  
Title:
Two new non-negativity preserving iterative regularization methods for solving inverse problems
Time & Venue:
2019.10.24 15:00-16:00 N202
Abstract:
In this talk, in order to obtain a stable non-negative approximate solution, we develop two novel non-negativity preserving iterative regularization methods. In contrast to the projected Landweber iteration, which has only weak convergence w.r.t. noise for the regularized solution, the newly introduced regularization methods exhibit the strong convergence. The convergence result for the imperfect forward model, as well as the convergence rates, are discussed. Two new discrepancy principles are developed for a posteriori stopping of our iterative regularization algorithms. As an application of our new approaches, we consider a biosensor problem, which is modelled as a two dimensional Fredholm integral equation of the first kind.
 

 

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