Antory, David, Kruger, Uwe and Littler, Tim (2006) A new principal curve algorithm for nonlinear principal component analysis. In: International Conference on Intelligent Computing (ICIC), Kunming, China, 6-19 Aug 2006. Published in: Lecture Notes in Computer Science, Volume 4113 pp. 1235-1246.

Full text not available from this repository.

Abstract

This paper summarizes a new concept to determine principal curves for nonlinear principal component analysis (PCA). The concept is explained within the framework of the Hastie and Stuetzle algorithm and utilizes spline functions. The paper proposes a new algorithm and shows that it provides an efficient method to extract underlying information from measured data. The new method is geometrically simple and computationally expedient, as the number of unknown parameters increases linearly with the analyzed variable set. The utility of the algorithm is exemplified in two examples.

Item Type:	Conference Item (Paper)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions:	Faculty of Science > WMG (Formerly the Warwick Manufacturing Group)
Series Name:	Lecture Notes in Computer Science
Journal or Publication Title:	Lecture Notes in Computer Science
Publisher:	Springer
ISBN:	978-3-540-37271-4
ISSN:	0302-9743
Editor:	Huang, DS and Li, K and Irwin, GW
Official Date:	2006
Dates:	Date Event 2006 Published
Volume:	Volume 4113
Number of Pages:	12
Page Range:	pp. 1235-1246
Identifier:	10.1007/11816157_155
Status:	Peer Reviewed
Publication Status:	Published
Conference Paper Type:	Paper
Title of Event:	International Conference on Intelligent Computing (ICIC)
Type of Event:	Conference
Location of Event:	Kunming, China
Date(s) of Event:	6-19 Aug 2006
URI:	http://wrap.warwick.ac.uk/id/eprint/5727

Data sourced from Thomson Reuters' Web of Knowledge

Request changes or add full text files to a record

Actions (login required)

View Item