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Particle filters and beamforming for EEG source estimation

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

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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: 23 Sep 2013 15:51
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/58601

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