Sezgin N.Ta?luk M.E.Tekin R.2024-08-042024-08-0420129781467300568https://doi.org/10.1109/SIU.2012.6204677https://hdl.handle.net/11616/922752012 20th Signal Processing and Communications Applications Conference, SIU 2012 -- 18 April 2012 through 20 April 2012 -- Fethiye, Mugla -- 90786Independent Component Analysis (ICA) is a statistical method used for separating nongaussian independent components of a mixture signal. In this study, by separating the signal into its possible independent components, the simplification and comprehension of analysis of EEG signals was aimed. Through such an analysis it was thought that early diagnosis of some neurological disease such as epilepsy, parkinson's disease, sleep disorders as well as information regarding the location and size of problematic zone may become possible. © 2012 IEEE.trinfo:eu-repo/semantics/closedAccessEEGFastICAIndependent component analysisKurtosisConference Object10.1109/SIU.2012.62046772-s2.0-84863449353N/A