Convergence and Complexity Analysis of a Levenberg–Marquardt Algorithm for Inverse Problems

The Levenberg–Marquardt algorithm is one of the most popular algorithms for finding the solution of nonlinear least squares problems. Across different modified variations of the basic procedure, the algorithm enjoys global convergence, a competitive worst-case iteration complexity rate, and a guaran...

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Veröffentlicht in:	Journal of optimization theory and applications Jg. 185; H. 3; S. 927 - 944
Hauptverfasser:	Bergou, El Houcine, Diouane, Youssef, Kungurtsev, Vyacheslav
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.06.2020 Springer Nature B.V Springer Verlag
Schlagworte:	Algorithms Applications of Mathematics Basic converters Calculus of Variations and Optimal Control; Optimization Complexity Convergence Engineering General Mathematics Inverse problems Iterative methods Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Theory of Computation Levenberg–Marquardt method Inverse problems Global and local convergence Worst-case complexity bound 90C06 49M05 49M15 90C60
ISSN:	0022-3239, 1573-2878
Online-Zugang:	Volltext
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