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IJCNN
2006
IEEE
14 years 1 months ago
Nonlinear Component Analysis Based on Correntropy
Abstract— In this paper, we propose a new nonlinear principal component analysis based on a generalized correlation function which we call correntropy. The data is nonlinearly tr...
Jian-Wu Xu, Puskal P. Pokharel, António R. ...
CSDA
2004
105views more  CSDA 2004»
13 years 7 months ago
Computational aspects of algorithms for variable selection in the context of principal components
Variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. Several...
Jorge Cadima, J. Orestes Cerdeira, Manuel Minhoto
ICPR
2006
IEEE
14 years 8 months ago
Texture Segmentation Using Independent Component Analysis of Gabor Features
This paper proposes a novel method for texture segmentation using independent component analysis (ICA) of Gabor features (called ICAG). It has three distinguished aspects. (1) Gab...
Yang Chen, Runsheng Wang
ICANN
1997
Springer
13 years 11 months ago
Kernel Principal Component Analysis
A new method for performing a nonlinear form of Principal Component Analysis is proposed. By the use of integral operator kernel functions, one can e ciently compute principal comp...
Bernhard Schölkopf, Alex J. Smola, Klaus-Robe...
CNSR
2011
IEEE
257views Communications» more  CNSR 2011»
12 years 11 months ago
On Threshold Selection for Principal Component Based Network Anomaly Detection
—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...
Petar Djukic, Biswajit Nandy