Georgieva, Petia and Mihaylova, Lyudmila and Bouaynaya, Nidhal and Jain, Lakhmi (2012) Particle filters and beamforming for EEG source estimation. In: Neural Networks (IJCNN), The 2012 International Joint Conference on. IEEE, Brisbane, Australia, pp. 1-8. ISBN 978-1-4673-1488-6
Full text not available from this repository.Official URL: http://dx.doi.org/10.1109/IJCNN.2012.6252516
Abstract
This is a proof of concept work that proposes a solution to the inverse problem of EEG source estimation by combining two techniques, namely a Particle Filter (PF) for geometrical (3D) localization of the most active brain zones (expressed by two dipoles) and a beamformer (BF) as a spatial filter for estimation of the oscillations that have originated the recorded EEG data. The estimation is reliable for uncorrelated brain sources.
| Item Type: | Contribution in Book/Report/Proceedings |
|---|---|
| Uncontrolled Keywords: | EEG ; Source localisation ; Particle filter (PF) ; Beamforming ; Inverse problems ; brain electrical source localization ; filtering and state estimation ; hidden markov models |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Departments: | Faculty of Science and Technology > School of Computing & Communications |
| ID Code: | 58601 |
| Deposited By: | ep_importer_pure |
| Deposited On: | 25 Sep 2012 10:21 |
| Refereed?: | No |
| Published?: | Published |
| Last Modified: | 25 Sep 2012 10:21 |
| Identification Number: | |
| URI: | http://eprints.lancs.ac.uk/id/eprint/58601 |
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