An algorithm for solving sparse nonlinear least squares problems (Q1822462)
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scientific article; zbMATH DE number 4003385
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | An algorithm for solving sparse nonlinear least squares problems |
scientific article; zbMATH DE number 4003385 |
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An algorithm for solving sparse nonlinear least squares problems (English)
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1987
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We introduce a new method for solving nonlinear least squares problems when the Jacobian matrix of the system is large and sparse. The main features of the new method are the following: a) The Gauss-Newton equation is ''partially'' solved at each iteration using a preconditioned conjugate gradient algorithm. b) The new point is obtained using a two- dimensional trust region scheme, similar to the one introduced by Bulteau and Vial. We prove global and local convergence results and we present some numerical experiments.
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large sparse Jacobian matrix
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Gauss-Newton method
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nonlinear least squares problems
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conjugate gradient algorithm
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trust region scheme
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global and local convergence
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numerical experiments
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preconditioning
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0.9436556
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0.9321052
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0.9302657
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0.92863536
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