Minimization of Linear Functionals Defined on| Solutions of Large-Scale Discrete Ill-Posed Problems

Lars Elden, Per Christian Hansen, Marielba Rojas

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    Abstract

    The minimization of linear functionals de ned on the solutions of discrete ill-posed problems arises, e.g., in the computation of con dence intervals for these solutions. In 1990, Elden proposed an algorithm for this minimization problem based on a parametric-programming reformulation involving the solution of a sequence of trust-region problems, and using matrix factorizations. In this paper, we describe MLFIP, a large-scale version of this algorithm where a limited-memory trust-region solver is used on the subproblems. We illustrate the use of our algorithm in connection with an inverse heat conduction problem.
    Original languageEnglish
    Publication statusPublished - 2003

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