Change point detection of EEG signals based on particle swarm optimization
This paper proposes a change point detection for electroencephalograms (EEG) signal application based on Particle Swarm Optimization (PSO). As EEG signal is well known consider as non-stationary in nature, we model the signal by using the sinusoidal-Heaviside function, which are capable to represent...
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| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://www.scopus.com/inward/record.url?eid=2-s2.0-79959971518&partnerID=40&md5=27b820845e94700034668241e77e97e1 http://link.springer.com/chapter/10.1007/978-3-642-21729-6₁₂₂ http://download.springer.com/static/pdf/344/chp253A10.1007252F978-3-642-21729-61 http://www.scopus.com/inward/record.url?eid=2-s2.0-79959971518&partnerID=40&md5=27b820845e94700034668241e77e97e1 http://link.springer.com/chapter/10.1007/978-3-642-21729-6₁₂₂ http://download.springer.com/static/pdf/344/chp253A10.1007252F978-3-642-21729-61 http://eprints.um.edu.my/9482/1/Change_Point_Detection_of_EEG_Signals_Based_on_Particle_Swarm_Optimization.pdf |
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