The q-Levenberg-Marquardt method for unconstrained nonlinear optimization
Optimization and Control
2021-07-08 v1 Numerical Analysis
Numerical Analysis
Abstract
A q-Levenberg-Marquardt method is an iterative procedure that blends a q-steepest descent and q-Gauss-Newton methods. When the current solution is far from the correct one the algorithm acts as the q-steepest descent method. Otherwise the algorithm acts as the q-Gauss-Newton method. A damping parameter is used to interpolate between these two methods. The q-parameter is used to escape from local minima and to speed up the search process near the optimal solution.
Cite
@article{arxiv.2107.03304,
title = {The q-Levenberg-Marquardt method for unconstrained nonlinear optimization},
author = {Danijela Protic and Miomir Stankovic},
journal= {arXiv preprint arXiv:2107.03304},
year = {2021}
}