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ICA
2004
Springer
15 years 3 months ago
Post-nonlinear Independent Component Analysis by Variational Bayesian Learning
Post-nonlinear (PNL) independent component analysis (ICA) is a generalisation of ICA where the observations are assumed to have been generated from independent sources by linear mi...
Alexander Ilin, Antti Honkela
IJCSS
2006
116views more  IJCSS 2006»
14 years 9 months ago
Extracting Motor Unit Firing Information by Independent Component Analysis of Surface Electromyogram: A Preliminary Study Using
Decomposition of electromyogram (EMG) provides a valuable means of obtaining motor unit recruitment and firing rate information. The feasibility of decomposing surface EMG signals...
Ping Zhou, M. M. Lowery, W. Zev Rymer
BMCBI
2008
135views more  BMCBI 2008»
14 years 9 months ago
Knowledge-guided multi-scale independent component analysis for biomarker identification
Background: Many statistical methods have been proposed to identify disease biomarkers from gene expression profiles. However, from gene expression profile data alone, statistical...
Li Chen, Jianhua Xuan, Chen Wang, Ie-Ming Shih, Yu...
ICASSP
2011
IEEE
14 years 1 months ago
Topographic phase maps using iterative independent component analysis
In this study, we employed our recently developed iterative independent component analysis (iICA) procedure to measure single-trial EPs from auditory N100 recordings of 21 normal ...
Darshan Iyer, George Zouridakis
NIPS
2004
14 years 11 months ago
Linear Multilayer Independent Component Analysis for Large Natural Scenes
In this paper, linear multilayer ICA (LMICA) is proposed for extracting independent components from quite high-dimensional observed signals such as large-size natural scenes. Ther...
Yoshitatsu Matsuda, Kazunori Yamaguchi