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IWINAC
2005
Springer
14 years 1 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...
ICPR
2008
IEEE
14 years 1 months ago
A network intrusion detection method using independent component analysis
An intrusion detection system (IDS) detects illegal manipulations of computer systems. In intrusion detection systems, feature reduction, including feature extraction and feature ...
Dayu Yang, Hairong Qi
NC
2007
129views Neural Networks» more  NC 2007»
13 years 7 months ago
Sorting of neural spikes: When wavelet based methods outperform principal component analysis
Sorting of the extracellularly recorded spikes is a basic prerequisite for analysis of the cooperative neural behavior and neural code. Fundamentally the sorting performance is deļ...
Alexey N. Pavlov, Valeri A. Makarov, Ioulia Makaro...
JMM2
2006
110views more  JMM2 2006»
13 years 7 months ago
Two-Stage PCA Extracts Spatiotemporal Features for Gait Recognition
We propose a technique for gait recognition from motion capture data based on two successive stages of principal component analysis (PCA) on kinematic data. The first stage of PCA ...
Sandhitsu R. Das, Robert C. Wilson, Maciej T. Laza...
NIPS
2008
13 years 9 months ago
Robust Kernel Principal Component Analysis
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...
Minh Hoai Nguyen, Fernando De la Torre