本文简要介绍了最小二乘法拟合的基本原理和公式推导过程，以及如何通过最小

This paper briefly describes the basic principles of least squares fit and the derivation of formulas and how nonlinear equation into a linear equation used to obtain the equation coefficients MATLAB software programming by addition of discrete data fitting the least squares method to solve . Herein is performed while satisfying the requirements of the subject with three different fitting function fit, and gives the least square error fit curve, and the corresponding results are compared curve fitting analysis and merits.

This paper briefly introduces the basic principle and formula derivation process of least-square-by-multiply, and how to solve the nonlinear equation into commonly used linear equations by using the least-square-multiply method, so as to obtain the equation coefficient through MATLAB software programming and then fit the discrete data. At the same time, this paper meets the requirements of the topic, but also with three different fitting functions for fitting, gives the fitting curve and the minimum square error, and compares and analyzes the corresponding curve fitting effect.

This paper briefly introduces the basic principle and formula derivation process of the least square fitting, and how to solve the nonlinear equation by the least square method into the common linear equation, so as to obtain the equation coefficient through MATLAB software programming and then fit the discrete data. In this paper, three different fitting functions are used to fit the questions, and the fitting curve and the least square error are given, and the corresponding curve fitting effect is compared and analyzed.<br>