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...
Analysis of causal effects between continuous-valued variables typically uses either autoregressive models or structural equation models with instantaneous effects. Estimation of ...
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...
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...
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...