A New Principal Curve Algorithm for Nonlinear Principal Component Analysis

D. Antory, Uwe Kruger, Timothy Littler

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper emerged from work supported by EPSRC grant GR/S84354/01 and proposes a method of determining principal curves, using spline functions, in principal component analysis (PCA) for the representation of non-linear behaviour in process monitoring. Although principal curves are well established, they are difficult to implement in practice if a large number of variables are analysed. The significant contribution of this paper is that the proposed method has minimal complexity, assuming simple spline geometry, thus enabling efficient computation. The paper provides a foundation for further work where multiple curves may be required to represent underlying non-linear information in complex data.
Original languageEnglish
Title of host publicationIntelligent Computing, Part I
Pages1235-1246
Number of pages12
Volume4113 (2006)
DOIs
Publication statusPublished - Sep 2006

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Theory and Mathematics

Fingerprint Dive into the research topics of 'A New Principal Curve Algorithm for Nonlinear Principal Component Analysis'. Together they form a unique fingerprint.

  • Cite this

    Antory, D., Kruger, U., & Littler, T. (2006). A New Principal Curve Algorithm for Nonlinear Principal Component Analysis. In Intelligent Computing, Part I (Vol. 4113 (2006), pp. 1235-1246) https://doi.org/10.1007/11816157_155