A New Principal Curve Algorithm for Nonlinear Principal Component Analysis

  • David Antory
  • Uwe Kruger
  • Tim Littler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4113)


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.


Principal Curve Spline Function Projection Stage Nonlinear Principal Component Analysis Spline Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • David Antory
    • 1
  • Uwe Kruger
    • 2
  • Tim Littler
    • 3
  1. 1.International Automotive Research CentreUniversity of WarwickCoventryU.K.
  2. 2.Intelligent Systems and Control GroupQueen’s UniversityBelfastU.K.
  3. 3.Energy Systems Research GroupQueen’s UniversityBelfastU.K.

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