An Improved Moving Least Squares Method for Curve and Surface Fitting. (20th November 2013)

• Record Type: Journal Article
• Authors: Zhang, Lei; Gu, Tianqi; Zhao, Ji; Ji, Shijun; Hu, Ming; Li, Xiangbo
• Other Names: Andrianov Igor Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2013(2013)
• Publication Date: 2013-11-20
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2013/159694
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : The moving least squares (MLS) method has been developed for the fitting of measured data contaminated with random error. The local approximants of MLS method only take the error of dependent variable into account, whereas the independent variable of measured data always contains random error. Considering the errors of all variables, this paper presents an improved moving least squares (IMLS) method to generate curve and surface for the measured data. In IMLS method, total least squares (TLS) with a parameter λ based on singular value decomposition is introduced to the local approximants. A procedure is developed to determine the parameter λ . Numerical examples for curve and surface fitting are given to prove the performance of IMLS method.