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» A Constraint Learning Algorithm for Blind Source Separation
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ICA
2007
Springer
14 years 1 months ago
A Robust Complex FastICA Algorithm Using the Huber M-Estimator Cost Function
In this paper, we propose to use the Huber M-estimator cost function as a contrast function within the complex FastICA algorithm of Bingham and Hyvarinen for the blind separation o...
Jih-Cheng Chao, Scott C. Douglas
ESANN
2006
13 years 9 months ago
Non-orthogonal Support Width ICA
Independent Component Analysis (ICA) is a powerful tool with applications in many areas of blind signal processing; however, its key assumption, i.e. the statistical independence o...
John Aldo Lee, Frédéric Vrins, Miche...
PRIB
2009
Springer
209views Bioinformatics» more  PRIB 2009»
14 years 2 months ago
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm
For many biomedical modelling tasks a number of different types of data may influence predictions made by the model. An established approach to pursuing supervised learning with ...
Yiming Ying, Colin Campbell, Theodoros Damoulas, M...
ICA
2012
Springer
12 years 3 months ago
Distributional Convergence of Subspace Estimates in FastICA: A Bootstrap Study
Independent component analysis (ICA) is possibly the most widespread approach to solve the blind source separation (BSS) problem. Many different algorithms have been proposed, tog...
Jarkko Ylipaavalniemi, Nima Reyhani, Ricardo Vig&a...
ISBI
2008
IEEE
14 years 8 months ago
Blind deconvolution for diffraction-limited fluorescence microscopy
Optical Sections of biological samples obtained from a fluorescence Confocal Laser Scanning Microscopes (CLSM) are often degraded by out-of-focus blur and photon counting noise. S...
Praveen Pankajakshan, Bo Zhang, Laure Blanc-F&eacu...