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On the inexactness level of robust Levenberg-Marquardt methods

Andreas Fischer, Pradyumn Kumar Shukla, M. Wang

Veröffentlicht: 2010 Februar

Journal: Optimization
Nummer: 2
Seiten: 273 - 287
Verlag: Taylor & Francis
Volume: 59

Referierte Veröffentlichung

Recently, the Levenberg-Marquardt (LM) method has been used for solving systems of nonlinear equations with nonisolated solutions. Under certain conditions it converges Q-quadratically to a solution. The same rate has been obtained for inexact versions of the LM method. In this article the LM method will be called robust, if the magnitude of the regularization parameter occurring in its sub-problems is as large as possible without decreasing the convergence rate. For robust LM methods the article shows that the level of inexactness in the sub-problems can be increased significantly. As an application, the local convergence of a projected robust LM method is analysed.


Effiziente Algorithmen

Multikriterielle Optimierung