Nonlinear Least Squares Curre Fitting

dc.contributor.author	楊壬孝	zh_tw
dc.date.accessioned	2014-10-27T15:24:14Z
dc.date.available	2014-10-27T15:24:14Z
dc.date.issued	1988-06-??	zh_TW
dc.description.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。	zh_tw
dc.description.abstract	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.	en_US
dc.identifier	62ED7B9B-0651-6687-8C04-D233C1E73080	zh_TW
dc.identifier.uri	http://rportal.lib.ntnu.edu.tw/handle/20.500.12235/17232
dc.language	英文	zh_TW
dc.publisher	國立臺灣師範大學研究發展處	zh_tw
dc.publisher	Office of Research and Development	en_US
dc.relation	(33)，329-345	zh_TW
dc.relation.ispartof	師大學報	zh_tw
dc.subject.other	非線性最小平方法	zh_tw
dc.subject.other	最適曲線	zh_tw
dc.title	Nonlinear Least Squares Curre Fitting	zh-tw
dc.title.alternative	非線性最小平方法之最適曲線	zh_tw

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