Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
696717 | Automatica | 2010 | 7 Pages |
Abstract
Projection to latent structures or partial least squares (PLS) produces output-supervised decomposition on input X, while principal component analysis (PCA) produces unsupervised decomposition of input X. In this paper, the effect of output Y on the X-space decomposition in PLS is analyzed and geometric properties of the PLS structure are revealed. Several PLS algorithms are compared in a geometric way for the purpose of process monitoring. A numerical example and a case study are given to illustrate the analysis results.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Gang Li, S. Joe Qin, Donghua Zhou,