Original title: A Hybrid Method for Nonlinear Least Squares that Uses Quasi-Newton Updates Applied to an Approximation of the Jacobian Matrix
Authors: Lukšan, Ladislav ; Vlček, Jan
Document type: Papers
Conference/Event: Programs and Algorithms of Numerical Mathematics /19./, Hejnice (CZ), 20180624
Year: 2019
Language: eng
Abstract: In this contribution, we propose a new hybrid method for minimization of nonlinear least squares. This method is based on quasi-Newton updates, applied to an approximation A of the Jacobian matrix J, such that AT f = JT f. This property allows us to solve a linear least squares problem, minimizing ∥Ad+f∥ instead of solving the normal equation ATAd+JT f = 0, where d ∈ Rn is the required direction vector. Computational experiments confirm the efficiency of the new method.
Keywords: hybrid methods; nonlinear least squares; numerical algorithms; numerical experiments; quasi-Newton methods; trust-region methods
Host item entry: Programs and Algorithms of Numerical Mathematics 19, ISBN 978-80-85823-69-1

Institution: Institute of Computer Science AS ČR (web)
Document availability information: Fulltext is available at the institute of the Academy of Sciences.
Original record: http://hdl.handle.net/11104/0289769

Permalink: http://www.nusl.cz/ntk/nusl-391451

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Research > Institutes ASCR > Institute of Computer Science
Conference materials > Papers
 Record created 2019-02-13, last modified 2020-12-03

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