title: AR spectral analysis of EEG signals by using maximum likelihood estimation.
abstract: In this study, EEG signals were analyzed using autoregressive (AR) method. Parameters in AR method were realized by using maximum likelihood estimation (MLE). Results were compared with fast Fourier transform (FFT) method. It is observed that AR method gives better results in the analysis of EEG signals. On the other hand, the results have also showed that AR method can also be used for some other researches and diagnosis of diseases.
authors.affiliation: Department of Electronics-Computer Education, Faculty of Technical Education, Gazi University, 06500 Teknikokullar, Ankara, Turkey. iguler@tef.gazi.edu.tr
authors.forename: I
authors.initials: I
authors.lastname: Güler
authors.forename: M K
authors.initials: MK
authors.lastname: Kiymik
authors.forename: M
authors.initials: M
authors.lastname: Akin
authors.forename: A
authors.initials: A
authors.lastname: Alkan
mesh_terms: D001927:Brain Diseases / Q000175:diagnosis / Q000503:physiopathology; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted; D004569:Electroencephalography / Q000706:statistics & numerical data*; D004827:Epilepsy / Q000175:diagnosis / Q000503:physiopathology; D005583:Fourier Analysis; D006801:Humans; D016013:Likelihood Functions; D012044:Regression Analysis; D012815:Signal Processing, Computer-Assisted