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» ICA for Noisy Neurobiological Data
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IJCNN
2000
IEEE
13 years 8 months ago
ICA for Noisy Neurobiological Data
ICA (Independent Component Analysis) is a new technique for analyzing multi-variant data. Lots of results are reported in the field of neurobiological data analysis such as EEG (...
Shiro Ikeda, Keisuke Toyama
NN
2000
Springer
159views Neural Networks» more  NN 2000»
13 years 3 months ago
Independent component analysis for noisy data -- MEG data analysis
ICA (independent component analysis) is a new, simple and powerful idea for analyzing multi-variant data. One of the successful applications is neurobiological data analysis such ...
Shiro Ikeda, Keisuke Toyama
ICASSP
2010
IEEE
13 years 1 months ago
Phase correction and denoising for ICA of complex FMRI data
Analysis of functional magnetic resonance imaging (fMRI) data in its native, complex form has been shown to increase the sensitivity of the analysis both for data driven technique...
Pedro Rodriguez, Tülay Adali, Hualiang Li, Ni...
ICASSP
2011
IEEE
12 years 7 months ago
On the relation between ICA and MMSE based source separation
This paper aims at deriving a relationship between minimum mean square error (MMSE) based source separation and independent component analysis (ICA) based on the Kullback-Leibler ...
Benedikt Loesch, Bin Yang
IWANN
2005
Springer
13 years 9 months ago
Co-evolutionary Learning in Liquid Architectures
A large class of problems requires real-time processing of complex temporal inputs in real-time. These are difficult tasks for state-of-the-art techniques, since they require captu...
Igal Raichelgauz, Karina Odinaev, Yehoshua Y. Zeev...