Cura O.K.Ozdemir M.A.Akan A.Pehlivan S.2023-06-162023-06-1620219.79E+122219-5491https://doi.org/10.23919/Eusipco47968.2020.9287719https://hdl.handle.net/20.500.14365/373328th European Signal Processing Conference, EUSIPCO 2020 -- 24 August 2020 through 28 August 2020 -- 165944Epilepsy is a neurological disorder that affects many people all around the world, and its early detection is a topic of research widely studied in signal processing community. In this paper, a new technique that was introduced to solve problems of fluid dynamics called Dynamic Mode Decomposition (DMD), is used to classify seizure and non-seizure epileptic EEG signals. The DMD decomposes a given signal into the intrinsic oscillations called modes which are used to define a DMD spectrum. In the proposed approach, the DMD spectrum is obtained by applying either multi-channel or single-channel based DMD technique. Then, subband and total power features extracted from the DMD spectrum and various classifiers are utilized to classify seizure and non-seizure epileptic EEG segments. Outstanding classification results are achieved by both the single-channel based (96.7%), and the multi-channel based (96%) DMD approaches. © 2021 European Signal Processing Conference, EUSIPCO. All rights reserved.eninfo:eu-repo/semantics/closedAccessDMD spectrumDynamic mode decomposition (DMD)Epileptic EEG classificationNeurologyClassification resultsDynamic mode decompositionsEpileptic EEGIntrinsic oscillationsMulti channelNeurological disordersSingle channelsTotal powerBiomedical signal processingConference Object10.23919/Eusipco47968.2020.92877192-s2.0-85099312132