Publication Date:
2019-06-28
Description:
A Gauss-Newton algorithm is presented for solving nonlinear least squares problems. The problem statement may include simple bounds or more general constraints on the unknowns. The algorithm uses a trust region that allows the objective function to increase with logic for retreating to best values. The computations for the linear problem are done using a least squares system solver that allows for simple bounds and linear constraints. The trust region limits are defined by a box around the current point. In its current form the algorithm is effective only for problems with small residuals, linear constraints and dense Jacobian matrices. Results on a set of test problems are encouraging.
Keywords:
NUMERICAL ANALYSIS
Type:
NASA-CR-174480
,
NAS 1.26:174480
,
DE83-016773
,
SAND-83-0936-PT-1
Format:
application/pdf
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