最小二乘曲线拟合及Matlab实现

采用最小二乘曲线拟合,可寻求有限测量数据及其伴随误差的变化规律.曲线拟合先确定拟合模型,再确定函数的所属类.多项式拟合先将其化为双曲线、S型曲线、倒指数曲线、对数曲线等拟合曲线,再求解拟合多项式系数.并用Matlab编制程序,对测量数据进行拟合与仿真.

Curve Fitting in Least-Square Method and Its Realization with Matlab

Least-square curve fitting method is used to seek the changing rule of the definite measured data and its concomitant error. Fitting model is decided firstly, and the belonged class of fitting function is decided. For polynomial fitting method, polynomial was changed into fitting curves of hyperbola, S-figure curve, converse exponential curve and logarithm curve, etc. And polynomial coefficient was solved, the polynomial modulus was programmed by Matlab. Measured data was fitted and simulated with this program.