2025/09/16 by Pes, Federica, Rodriguez, Giuseppe
#Gauss-Newton method #nonlinear least-squares #regularization
paper · doi:10.13135/3103-1935/11898
This paper describes a Matlab toolbox designed to solve nonlinear least-squares problems, with a particular focus on ill-posed cases lacking unique solution, allowing to obtain the minimal-norm solution. The algorithm is based on the Gauss-Newton method, in which the iteration is modified introducing a projection term onto the null space of the Jacobian of the nonlinear function. To address the severe ill-conditioning often encountered in real-world applications, the toolbox also includes some regularization techniques.