Nonlinear Least Squares Curre Fitting
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Date
1988-06-??
Authors
楊壬孝
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Publisher
國立臺灣師範大學研究發展處
Office of Research and Development
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.
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.