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WSCG
2004
188views more  WSCG 2004»
13 years 9 months ago
Recognition of Motor Imagery Electroencephalography Using Independent Component Analysis and Machine Classifiers
Motor imagery electroencephalography (EEG), which embodies cortical potentials during mental simulation of left or right finger lifting tasks, can be used as neural input signals ...
Chih-I. Hung, Po-Lei Lee, Yu-Te Wu, Hui-Yun Chen, ...
PDP
2008
IEEE
14 years 2 months ago
Behavioural Skeletons in GCM: Autonomic Management of Grid Components
Autonomic management can be used to improve the QoS provided by parallel/distributed applications. We discuss behavioural skeletons introduced in earlier work: rather than relying...
Marco Aldinucci, Sonia Campa, Marco Danelutto, Mar...
IBPRIA
2003
Springer
14 years 1 months ago
Does Independent Component Analysis Play a~Role in Unmixing Hyperspectral Data?
—Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a li...
José M. P. Nascimento, José M. B. Di...
BMCBI
2006
183views more  BMCBI 2006»
13 years 8 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
BMCBI
2005
201views more  BMCBI 2005»
13 years 8 months ago
Principal component analysis for predicting transcription-factor binding motifs from array-derived data
Background: The responses to interleukin 1 (IL-1) in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to...
Yunlong Liu, Matthew P. Vincenti, Hiroki Yokota