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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Source Files
Filename | Size | Changed |
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_link | 0000000124 124 Bytes | 4 months |
levmar-2.6.tgz | 0000081143 79.2 KB | almost 7 years |
levmar.changes | 0000001556 1.52 KB | 4 months |
levmar.spec | 0000004399 4.3 KB | 4 months |
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