Travelling source estimation using spatio-temporal data

Abstract

The estimation of travelling source parameters takes a considerable importance for many areas of sensor space-array procesing, e.g., radar, underwater acoustic, non-invasive electro-medicine. State-space models are a wall suited framework for solving that dynamic estimation problem and they are in the core of our studies. The parameter estimation problem is solved by analyzing spatio-temporal data, in applications where a relative large amount of noisy data is available. Part of our project is to analyze the conjunction of state-space models and spatio-temporal data technique will be used for the estimation of travelling brain sources from EEG/MEG measurees