199 search results - page 5 / 40 » Skew Detection via Principal Components Analysis |
CNSR
2011
IEEE
12 years 11 months ago
2011
IEEE
—Principal component based anomaly detection has emerged as an important statistical tool for network anomaly detection. It works by projecting summary network information onto a...
BMCBI
2011
12 years 11 months ago
2011
Background: The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used ...
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...
NIPS
2008
13 years 9 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
HAPTICS
2007
IEEE
14 years 1 months ago
2007
IEEE
A method based on Principal Component Analysis of the fingernail coloration pattern is presented to infer fingertip force direction during planar contact. Images from 7 subjects...