157 search results - page 4 / 32 » Applying Discrete PCA in Data Analysis |
TIFS
2008
13 years 7 months ago
2008
Performance of biometric-based recognition systems depends on various factors: database quality, image preprocessing, encoding techniques, etc. Given a biometric database and a se...
GLOBECOM
2009
IEEE
14 years 2 months ago
2009
IEEE
—In this paper we look at the problem of accurately reconstructing distributed signals through the collection of a small number of samples at a data gathering point. The techniqu...
AMCS
2008
13 years 7 months ago
2008
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...
JMLR
2010
13 years 2 months ago
2010
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
ECCV
2002
Springer
14 years 9 months ago
2002
Springer
Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...