921 search results - page 18 / 185 » Kernel Principal Component Analysis |
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...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy -- even on parallel processors -- unlike the...
ISNN
2004
Springer
14 years 29 days ago
2004
Springer
Abstract. Principal Component Analysis (PCA) is a feature extraction approach directly based on a whole vector pattern and acquires a set of projections that can realize the best r...
ECML
2007
Springer
13 years 11 months ago
2007
Springer
Recently, a successful extension of Principal Component Analysis for structured input, such as sequences, trees, and graphs, has been proposed. This allows the embedding of discret...
ICIP
2005
IEEE
14 years 9 months ago
2005
IEEE
In this paper, we present a novel algorithm for incremental principal component analysis. Based on the LargestEigenvalue-Theory, i.e. the eigenvector associated with the largest ei...