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.
|Title of host publication||Intelligent Computing, Part I|
|Number of pages||12|
|Publication status||Published - Sep 2006|
ASJC Scopus subject areas
- Control and Systems Engineering
- Computational Theory and Mathematics
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