AR spectral analysis of EEG signals by using maximum likelihood estimation

Computers in Biology and Medicine

Volumn 31, Issue 6, 2001, Pages 441-450

  Güler, İnan ^a,b,c   Kiymik, M Kemal ^a,b,c   Akin, Mehmet ^a,b,c   Alkan, Ahmet ^a,b,c  

^a GAZI UNIVERSITY   (Turkey)

^b KAHRAMANMARAS SUTCU IMAM UNIVERSITY   (Turkey)

^c DICLE UNIVERSITY   (Turkey)

Author keywords

Autoregressive method (AR); EEG; Fast Fourier transform (FFT); Maximum likelihood estimation (MLE)

Indexed keywords

FAST FOURIER TRANSFORMS; MAXIMUM LIKELIHOOD ESTIMATION; REGRESSION ANALYSIS; SPECTRUM ANALYSIS;

SIGNAL ANALYSIS;

ELECTROENCEPHALOGRAPHY;

ACCURACY; ARTICLE; DATA ANALYSIS; DIAGNOSTIC PROCEDURE; ELECTROENCEPHALOGRAM; FOURIER TRANSFORMATION; MATHEMATICAL COMPUTING; MAXIMUM LIKELIHOOD METHOD; PRIORITY JOURNAL; SPECTROSCOPY;

BRAIN DISEASES; COMPUTER SIMULATION; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROENCEPHALOGRAPHY; EPILEPSY; FOURIER ANALYSIS; HUMANS; LIKELIHOOD FUNCTIONS; REGRESSION ANALYSIS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 0034796777     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0010-4825(01)00022-1     Document Type: Article

References (10)

1. Seizure detection of newborn EEG using a model approach
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4. Comparison of FFT and AR-based sonogram outputs of 20 MHz pulsed Doppler data in real time
5. Some relations between the various criteria for AR model order determination
6. A general lower bound for parametric spectrum estimation
7. Maximum likelihood from incomplete data via the EM algorithm