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» Modeling non-gaussian noise for robust image analysis
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DAGM
2006
Springer
13 years 11 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...
JMLR
2010
134views more  JMLR 2010»
13 years 2 months ago
Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity
Analysis of causal effects between continuous-valued variables typically uses either autoregressive models or structural equation models with instantaneous effects. Estimation of ...
Aapo Hyvärinen, Kun Zhang, Shohei Shimizu, Pa...
SSIAI
2000
IEEE
13 years 12 months ago
Unsupervised Dempster-Shafer Fusion of Dependent Sensors
This paper deals with the problem of statistical unsupervised fusion of dependent sensors with its potential applications to multisensor image segmentation. On the one hand, Bayes...
Wojciech Pieczynski
ICASSP
2008
IEEE
14 years 1 months ago
A nonparametric minimum entropy image deblurring algorithm
In this paper we address the image restoration problem in the variational framework. Classical approaches minimize the Lp norm of the residual and rely on parametric assumptions o...
Cesario Vincenzo Angelino, Eric Debreuve, Michel B...
ISBI
2004
IEEE
14 years 8 months ago
Probabilistic ICA for fMRI
Independent Component Analysis is becoming a popular exploratory method for analysing complex data such as that from FMRI experiments. The application of such `model-free' me...
Christian Beckmann