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...
Guardado en:
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2002
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/22073 |
| Aporte de: |
| 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 |
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