119 search results - page 1 / 24 » Constrained Projection Approximation Algorithms for Principa... |
NPL
2006
13 years 10 months ago
2006
Abstract. In this paper we introduce a new error measure, integrated reconstruction error (IRE) and show that the minimization of IRE leads to principal eigenvectors (without rotat...
CVPR
2003
IEEE
15 years 25 days ago
2003
IEEE
When performing subspace modelling of data using Principal Component Analysis (PCA) it may be desirable to constrain certain directions to be more meaningful in the context of the...
DCC
2009
IEEE
14 years 11 months ago
2009
IEEE
An analysis is presented that extends existing Rayleigh-Ritz theory to the special case of highly eccentric distributions. Specifically, a bound on the angle between the first Rit...
CORR
2010
Springer
13 years 11 months ago
2010
Springer
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...
DCC
2008
IEEE
14 years 10 months ago
2008
IEEE
A method is proposed for the compression of hyperspectral signature vectors on severely resourceconstrained encoding platforms. The proposed technique, compressive-projection prin...