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levmar

Levenberg-Marquardt nonlinear least squares algorithm

levmar is a native ANSI C implementation of the Levenberg-Marquardt optimization algorithm. Both unconstrained and constrained (under linear equations, inequality and box constraints) Levenberg-Marquardt variants are included. The LM algorithm is an iterative technique that finds a local minimum of a function that is expressed as the sum of squares of nonlinear functions. It has become a standard technique for nonlinear least-squares problems and can be thought of as a combination of steepest descent and the Gauss-Newton method. When the current solution is far from the correct on, the algorithm behaves like a steepest descent method: slow, but guaranteed to converge. When the current solution is close to the correct solution, it becomes a Gauss-Newton method.
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Package version:2.5
Architecture:src
Distribution:Fedora
Filename:levmar-2.5-6.fc17.src.rpm

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1.36 KB2014-11-29HEADER  view  39 mirrors
76.97 KB2014-11-29levmar-2.5.tgz  view  24 mirrors
2.38 KB2014-11-29levmar-shared.patch  view
3.21 KB2014-11-29levmar.spec  view

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