基于最小二乘法的曲线拟合研究  

Study on Curve Fitting Based on Least Square Method

作　　者：陈良波[1] 郑亚青[1] 

机构地区：[1]华侨大学机电学院,福建厦门361100

出　　处：《无锡职业技术学院学报》2012年第5期52-55,共4页Journal of Wuxi Institute of Technology

摘　　要：在工程应用和科学实验中,曲线拟合是对系统做出结论或预测的重要手段。因此拟合误差变得非常重要,而最小二乘法作为曲线拟合最常用的方法,因其更为准确、实用而被广泛应用。该文就最小二乘法对实验所获得的数据进行曲线拟合,并对整个拟合过程进行归纳和总结,其中一些主要步骤是在Matlab中实现的。In engineering applications and scientific experiments, curving fitting is an important method to make a summary or prediction for a system. Therefore, the error of curving fitting becomes extremely im- portant. The most popular method in curving fitting is least square method, which is widely used because it is more accurate and practical. The article curve-fits the data of experiment by way of least square meth od, and concludes and summarizes the whole process of curving fitting, in which some main procedures are processed in matlab.

关 键 词：曲线拟合 最小二乘法 拟合误差 MATLAB 

分 类 号：O241.5[理学—计算数学]