Truncated Gauss-Newton algorithms for ill-conditioned nonlinear least squares problems
2004 (English)In: Optimization Methods & Software, Vol. 19, no 6, 721-737 p.Article in journal (Refereed) Published
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.
IdentifiersURN: urn:nbn:se:umu:diva-21928ISBN: 1055-6788OAI: oai:DiVA.org:umu-21928DiVA: diva2:212183