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ICASSP
2011
IEEE
12 years 8 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
ICA
2010
Springer
13 years 5 months ago
Adaptive Underdetermined ICA for Handling an Unknown Number of Sources
Independent Component Analysis is the best known method for solving blind source separation problems. In general, the number of sources must be known in advance. In many cases, pre...
Andreas Sandmair, Alam Zaib, Fernando Puente Le&oa...
ICA
2004
Springer
13 years 9 months ago
Postnonlinear Overcomplete Blind Source Separation Using Sparse Sources
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
Fabian J. Theis, Shun-ichi Amari
BMCBI
2006
203views more  BMCBI 2006»
13 years 4 months ago
Independent component analysis reveals new and biologically significant structures in micro array data
Background: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem...
Attila Frigyesi, Srinivas Veerla, David Lindgren, ...
ICASSP
2011
IEEE
12 years 8 months ago
Distributed blind source separation with an application to audio signals
A scalable blind source separation paradigm aimed at sensor networks is described. The approach facilitates an unlimited number of sensors and sources and does not require a fusio...
Yusuke Hioka, W. Bastiaan Kleijn