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Nonlinear optimization as it applies to curvefitting

Posted on:2015-12-11Degree:M.SType:Thesis
University:Southern Illinois University at CarbondaleCandidate:Callen, BryanFull Text:PDF
GTID:2470390017499113Subject:Mathematics
Abstract/Summary:
The purpose of this thesis is to examine different methods of curve-fitting through the process of nonlinear least squares. Specifically, Newton's method, Gauss Newton's method, Levenberg-Marquardt, Quasi Newton methods, and Nonlinear Conjugate Gradient method. The differing convergence rates, as well as necessary initial conditions are explored for a variety of methods. The concepts of the line search and trust region are also examined.
Keywords/Search Tags:Nonlinear, Methods
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