Electronic Resource
Springer
Journal of optimization theory and applications
18 (1976), S. 469-483
ISSN:
1573-2878
Keywords:
Nonlinear least-square problems
;
parameter optimization
;
penalty function methods
;
mathematical programming
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract An algorithm for solving the general nonlinear least-square problem is developed. An estimate for the Hessian matrix is constructed as the sum of two matrices. The first matrix is the usual first-order estimate used by the Gauss method, while the second matrix is generated recursively using a rank-one formula. Test results indicate that the method is superior to the standard Gauss method and compares favorably with other methods, especially for problems with nonzero residuals at the solution.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00932656
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