ERP source reconstruction by using Particle Swarm Optimization

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buir.contributor.authorArıkan, Orhan
buir.contributor.orcidArıkan, Orhan|0000-0002-3698-8888
dc.citation.epage368en_US
dc.citation.spage365en_US
dc.contributor.authorAlp, Yaşar Kemalen_US
dc.contributor.authorArıkan, Orhanen_US
dc.contributor.authorKarakaş, S.en_US
dc.coverage.spatialTaipei, Taiwanen_US
dc.date.accessioned2016-02-08T12:28:21Z
dc.date.available2016-02-08T12:28:21Z
dc.date.issued2009en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 19-24 April 2009en_US
dc.descriptionConference Name: International Conference on Acoustics, Speech and Signal Processing, IEEE 2009en_US
dc.description.abstractLocalization of the sources of Event Related Potentials (ERP) is a challenging inverse problem, especially to resolve sources of neural activity occurring simultaneously. By using an effective dipole source model, we propose a new technique for accurate source localization of ERP signals. The parameters of the dipole ERP sources are optimally chosen by using Particle Swarm Optimization technique. Obtained results on synthetic data sets show that proposed method well localizes the dipoles on their actual locations. On real data sets, the fit error between the actual and reconstructed data is successfully reduced to noise level by localizing a few dipoles in the brain.en_US
dc.identifier.doi10.1109/ICASSP.2009.4959596en_US
dc.identifier.issn1520-6149en_US
dc.identifier.urihttp://hdl.handle.net/11693/28739
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttps://doi.org/10.1109/ICASSP.2009.4959596en_US
dc.source.titleProceedings of the International Conference on Acoustics, Speech and Signal Processing, IEEE 2009en_US
dc.subjectAnalysis of neural activityen_US
dc.subjectERP source localizationen_US
dc.subjectParticle swarm optimization (PSO)en_US
dc.subjectParticle swarm optimization techniqueen_US
dc.subjectSource localizationen_US
dc.subjectSource reconstructionen_US
dc.subjectSynthetic datasetsen_US
dc.subjectEnterprise resource planningen_US
dc.titleERP source reconstruction by using Particle Swarm Optimizationen_US
dc.typeConference Paperen_US

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