89 search results - page 2 / 18 » Fast Independent Component Analysis in Kernel Feature Spaces |
JIPS
2007
13 years 4 months ago
2007
: Semantic clustering is important to various fields in the modern information society. In this work we applied the Independent Component Analysis method to the extraction of the f...
TNN
2008
13 years 4 months ago
2008
Abstract--Plenty of methods have been proposed in order to discover latent variables (features) in data sets. Such approaches include the principal component analysis (PCA), indepe...
NIPS
2008
13 years 6 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...
ICPR
2008
IEEE
13 years 11 months ago
2008
IEEE
An intrusion detection system (IDS) detects illegal manipulations of computer systems. In intrusion detection systems, feature reduction, including feature extraction and feature ...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
In this paper, we present a new independent component analysis mixture vector quantization (ICAMVQ) method to summarize the video content. In particular, independent component ana...