Dispersion data fitting based on Levenberg-Marquardt data fitting method

This article proposes a fitting method for three typical dispersion models. The method is based on the Levenberg-Marquardt (LM) algorithm, which is a mainstream nonlinear least squares method that provides good fitting accuracy and robustness. The dispersion model fitting method proposed in this article fits and solves key parameters for three typical dispersion models: Debye, Drude, and Lorentz models. The simulation results show that the method has good fitting effects for the three typical dispersion models.