We describe two regularization techniques based on optimal control for solving two types of ill-posed problems. We include convergence proofs of the regularization method and error estimates. We illustrate our method through problems in signal processing and parameter identification using an efficient Riccati solver. Our numerical results are compared to the same examples solved using Tikhonov regularization.
Editor-in-Chief: Kabanikhin, Sergey I.
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Optimal control as a regularization method for ill-posed problems
∗Department of Mathematics, UCLA, on leave from Industrial Mathematics Institute, University Linz, Altenbergerstr. 69, 4040 Linz, Austria. E-mail: kindermann@indmath.unilinz.ac.at
†Department of Mathematics, University of California, Los Angeles, CA 90095-1555, USA. E-mail: navasca@math.ucla.edu
Citation Information: Journal of Inverse and Ill-posed Problems jiip. Volume 14, Issue 7, Pages 685–703, ISSN (Online) 1569-3953, ISSN (Print) 0928-0219, DOI: 10.1515/156939406779802022,
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