A mixed least-squares method for an inverse problem of a nonlinear beam equation

Richard E. Ewing, Tao Lin, Yanping Lin

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)

Abstract

We discuss a finite-element method based on the mixed least-squares formulation. The cost functional turns out to be a polynomial so that its gradient and Hessian can be computed efficiently. A multi-level Newton iteration is introduced for minimizing the cost functional that can converge from a rough initial guess. Error estimates are derived which not only are optimal in a certain configuration, but also supply rules for choosing regularization parameters according to the mesh size and the random noise in the data.
Original languageEnglish
Pages (from-to)19-32
Number of pages14
JournalInverse Problems
Volume15
Issue number1
DOIs
Publication statusPublished - 1 Dec 1999
Externally publishedYes

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Signal Processing
  • Mathematical Physics
  • Computer Science Applications
  • Applied Mathematics

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