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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, 721-737 p.Article 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, 721-737 p.
Identifiers
URN: urn:nbn:se:umu:diva-21928ISBN: 1055-6788 OAI: oai:DiVA.org:umu-21928DiVA: diva2:212183
Available from: 2009-04-21 Created: 2009-04-21 Last updated: 2009-04-21

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CiteExportLink to record
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