Optimization Toolbox can solve linear and nonlinear least-squares problems, data fitting problems, and nonlinear equations.
The toolbox uses two algorithms for solving constrained linear least-squares problems:
The toolbox uses two algorithms for solving nonlinear least-squares problems:
The toolbox provides a specialized interface for data fitting problems in which you want to find the member of a family of nonlinear functions that best fits a set of data points. The toolbox uses the same algorithms for data fitting problems that it uses for nonlinear least-squares problems.
Optimization Toolbox implements a dogleg trust-region algorithm for solving a system of nonlinear equations where there are as many equations as unknowns. The toolbox can also solve this problem using the trust-region reflective and Levenberg-Marquardt algorithms.