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ICA
2007
Springer
15 years 11 months ago
Robust Independent Component Analysis Using Quadratic Negentropy
We present a robust algorithm for independent component analysis that uses the sum of marginal quadratic negentropies as a dependence measure. It can handle arbitrary source densit...
Jaehyung Lee, Taesu Kim, Soo-Young Lee
IEEEARES
2006
IEEE
15 years 10 months ago
Identifying Intrusions in Computer Networks with Principal Component Analysis
Most current anomaly Intrusion Detection Systems (IDSs) detect computer network behavior as normal or abnormal but cannot identify the type of attacks. Moreover, most current intr...
Wei Wang, Roberto Battiti
EWMF
2005
Springer
15 years 10 months ago
Discovering a Term Taxonomy from Term Similarities Using Principal Component Analysis
Abstract. We show that eigenvector decomposition can be used to extract a term taxonomy from a given collection of text documents. So far, methods based on eigenvector decompositio...
Holger Bast, Georges Dupret, Debapriyo Majumdar, B...
IWINAC
2005
Springer
15 years 10 months ago
Separation of Extracellular Spikes: When Wavelet Based Methods Outperform the Principle Component Analysis
spike separation is a basic prerequisite for analyzing of the cooperative neural behavior and neural code when registering extracelluIarly. Final performance of any spike sorting m...
Alexey N. Pavlov, Valeri A. Makarov, Ioulia Makaro...
SGAI
2005
Springer
15 years 10 months ago
The Effect of Principal Component Analysis on Machine Learning Accuracy with High Dimensional Spectral Data
This paper presents the results of an investigation into the use of machine learning methods for the identification of narcotics from Raman spectra. The classification of spectr...
Tom Howley, Michael G. Madden, Marie-Louise O'Conn...