Travelling source estimation using spatio-temporal data

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...

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Detalles Bibliográficos
Autor principal: Bria, Oscar N.
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2002
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Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/22073
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Sumario: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