levmar : Levenberg-Marquardt nonlinear least squares algorithms in C/C++ This site provides GPL native ANSI C implementations of the Levenberg-Marquardt optimization algorithm, usable also from C++, Matlab, Perl, Python, Haskell and Tcl and explains their use. Both unconstrained and constrained (under linear equations, inequality and box constraints) Levenberg-Marquardt variants are included. The Levenberg-Marquardt (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 one, 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.

References in zbMATH (referenced in 66 articles )

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  1. Araújo, G. H. M.; Arefidamghani, R.; Behling, R.; Bello-Cruz, Y.; Iusem, A.; Santos, L.-R.: Circumcentering approximate reflections for solving the convex feasibility problem (2022)
  2. Fischer, A.; Izmailov, A. F.; Jelitte, M.: Newton-type methods near critical solutions of piecewise smooth nonlinear equations (2021)
  3. Fischer, A.; Izmailov, A. F.; Jelitte, M.: Constrained Lipschitzian error bounds and noncritical solutions of constrained equations (2021)
  4. Gonçalves, Douglas S.; Gonçalves, Max L. N.; Oliveira, Fabrícia R.: An inexact projected LM type algorithm for solving convex constrained nonlinear equations (2021)
  5. Ke, Yifen; Ma, Changfeng; Zhang, Huai: A modified LM algorithm for tensor complementarity problems over the circular cone (2021)
  6. Pereira, Camila Leão; da Costa Neto, Ricardo Teixeira; Loiola, Bruna Rafaella: Cornering stiffness estimation using Levenberg-Marquardt approach (2021)
  7. Shifrin, E. I.; Popov, A. L.; Lebedev, I. M.; Chelyubeev, D. A.; Kozintsev, V. M.: Numerical and experimental verification of a method of identification of localized damages in a rod by natural frequencies of longitudinal vibration (2021)
  8. Sun, Hongchun; Wang, Yiju; Li, Shengjie; Sun, Min: An improvement on the global error bound estimation for ELCP and its applications (2021)
  9. Thiruvengadam, Sudharsan; Tan, Jei Shian; Miller, Karol: A generalised quaternion and Clifford algebra based mathematical methodology to effect multi-stage reassembling transformations in parallel robots (2021)
  10. Abubakar, Auwal Bala; Kumam, Poom; Mohammad, Hassan: A note on the spectral gradient projection method for nonlinear monotone equations with applications (2020)
  11. Shifrin, E. I.; Lebedev, I. M.: Identification of multiple cracks in a beam by natural frequencies (2020)
  12. Abubakar, Auwal Bala; Kumam, Poom; Awwal, Aliyu Muhammed: Global convergence via descent modified three-term conjugate gradient projection algorithm with applications to signal recovery (2019)
  13. Ahookhosh, Masoud; Aragón Artacho, Francisco J.; Fleming, Ronan M. T.; Vuong, Phan T.: Local convergence of the Levenberg-Marquardt method under Hölder metric subregularity (2019)
  14. Fischer, Andreas; Izmailov, Alexey F.; Solodov, Mikhail V.: Local attractors of Newton-type methods for constrained equations and complementarity problems with nonisolated solutions (2019)
  15. Guo, Jie; Wan, Zhong: A modified spectral PRP conjugate gradient projection method for solving large-scale monotone equations and its application in compressed sensing (2019)
  16. Ma, Xiang; Bi, Linfeng: A robust adaptive iterative ensemble smoother scheme for practical history matching applications (2019)
  17. Wang, Zhu-Jun; Cai, Li; Su, Yi-Fan; Peng, Zhen: An inexact affine scaling Levenberg-Marquardt method under local error bound conditions (2019)
  18. Galli, Leonardo; Kanzow, Christian; Sciandrone, Marco: A nonmonotone trust-region method for generalized Nash equilibrium and related problems with strong convergence properties (2018)
  19. Marini, Leopoldo; Morini, Benedetta; Porcelli, Margherita: Quasi-Newton methods for constrained nonlinear systems: complexity analysis and applications (2018)
  20. Mohammad, Mutaz; Lin, En-Bing: Gibbs effects using Daubechies and Coiflet tight framelet systems (2018)

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