Please use this identifier to cite or link to this item: http://rportal.lib.ntnu.edu.tw:80/handle/77345300/17232
Title: Nonlinear Least Squares Curre Fitting
Other Titles: 非線性最小平方法之最適曲線
Authors: 楊壬孝
Issue Date: Jun-1988
Publisher: 國立臺灣師範大學研究發展處
Office of Research and Development
Abstract: 由一群資料尋找最適曲線是科學分支中一重要的工作。於本文中,我們研究最小平方法(Least squares algorithm),辛普勒斯法(Simplex algorithm)及馬克特法(Marquardt's algorithm)並於IBM PC上實際比較其效率、精確度及其方法之適用性。
Fitting curves to data is an important task in various branches of science. In this paper, we investigate and implement (on an IBM-PC) the standard linear least squares algorithm, the simplex algorithm and Marquardt's algorithm. In particular, we shall compare the efficiency. accuracy, and general applicability of these algorithms.
URI: http://rportal.lib.ntnu.edu.tw//handle/77345300/17232
Other Identifiers: 62ED7B9B-0651-6687-8C04-D233C1E73080
Appears in Collections:師大學報

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