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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

Source Files

Filename Size Changed Actions
levmar-2.6.tgz 79.2 KB Download File
levmar.changes 918 Bytes Download File
levmar.spec 4.33 KB Download File

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