An improved sequential method for principal component analysis
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 1409-1415 |
Journal / Publication | Pattern Recognition Letters |
Volume | 24 |
Issue number | 9-10 |
Publication status | Published - Jun 2003 |
Link(s)
Abstract
In sequential principal component (PC) extraction, when increasing numbers of PCs are extracted the accumulated extraction error becomes dominant and makes a reliable extraction of the remaining PCs difficult. This paper presents an improved cascade recursive least squares method for PCs' extraction. The good features of the proposed approach are illustrated through simulation results, and include improved convergence speed and higher extraction accuracy. © 2002 Elsevier Science B.V. All rights reserved.
Research Area(s)
- Cascade recursive least squares (CRLS), Principal component analysis, Vector orthogonalization by subspace deflation
Citation Format(s)
An improved sequential method for principal component analysis. / Wang, Ze; Lee, Yin; Fiori, Simone et al.
In: Pattern Recognition Letters, Vol. 24, No. 9-10, 06.2003, p. 1409-1415.
In: Pattern Recognition Letters, Vol. 24, No. 9-10, 06.2003, p. 1409-1415.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review