Solution of ill-posed problems on sets of functions convex along all lines parallel to coordinate axes

  • V. Titarenko
  • , A. Yagola

    Research output: Contribution to journalArticlepeer-review

    Abstract

    In the paper we consider linear ill-posed problems on sets of functions convex upwards or downwards along all lines that belong to a functions' domain and are parallel to coordinate axes. A regularizing algorithm is constructed such that an approximate solution tends to the exact one uniformly of some subsets of the domain. The algorithms to estimate an error of finite dimensional approximation and to find a lower and an upper functions that bound all approximation solutions are provided. As a model example, an inverse problem for a two-dimensional heat conduction equation is solved. © 2008 de Gruyter.
    Original languageEnglish
    Pages (from-to)805-824
    Number of pages19
    JournalJournal of Inverse and Ill-Posed Problems
    Volume16
    Issue number8
    DOIs
    Publication statusPublished - Dec 2008

    Keywords

    • A priori information
    • Compact set
    • Convex function
    • Error estimation
    • Ill-posed problem

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