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Truncated Gauss-Newton algorithms for ill-conditioned nonlinear least squares problems
Umeå University, Faculty of Science and Technology, Departement of Computing Science.
Umeå University, Faculty of Science and Technology, Departement of Computing Science.
2004 (English)In: Optimization Methods & Software, Vol. 19, no 6, p. 721-737Article in journal (Refereed) Published
Abstract [en]

We address numerical optimization algorithms for solving nonlinear least squares problems that lack well-defined solutions, in particular discrete parameter estimation problems. We present algorithms based on the Gauss-Newton method for both exactly and almost rank-deficient problems. Merit functions proposed have good global convergence properties. Numerical results that confirm local convergence results are presented.

Place, publisher, year, edition, pages
2004. Vol. 19, no 6, p. 721-737
Identifiers
URN: urn:nbn:se:umu:diva-21928ISBN: 1055-6788 OAI: oai:DiVA.org:umu-21928DiVA, id: diva2:212183
Available from: 2009-04-21 Created: 2009-04-21 Last updated: 2009-04-21

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