Sciweavers

Share
230 search results - page 1 / 46
» Independent component analysis for noisy data -- MEG data an...
Sort
View
NN
2000
Springer
159views Neural Networks» more  NN 2000»
11 years 1 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
IJCNN
2000
IEEE
11 years 6 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
DAGM
2006
Springer
11 years 5 months ago
Robust MEG Source Localization of Event Related Potentials: Identifying Relevant Sources by Non-Gaussianity
Independent Component Analysis (ICA) is a frequently used preprocessing step in source localization of MEG and EEG data. By decomposing the measured data into maximally independent...
Peter Breun, Moritz Grosse-Wentrup, Wolfgang Utsch...
EOR
2011
172views more  EOR 2011»
10 years 8 months ago
Efficiency measurement using independent component analysis and data envelopment analysis
Efficiency measurement is an important issue for any firm or organization. Efficiency measurement allows organizations to compare their performance with their competitors’ and t...
Ling-Jing Kao, Chi-Jie Lu, Chih-Chou Chiu
MICCAI
2007
Springer
12 years 2 months ago
Sources of Variability in MEG
Abstract. This paper investigates and characterizes sources of variability in MEG signals in multi-site, multi-subject studies. Understanding these sources will help to develop eff...
Matti Hämäläinen, Polina Golland, W...
books