Digital signal processing (3rd ed.): principles, algorithms, and applications
Digital signal processing (3rd ed.): principles, algorithms, and applications
Comparison of Wavelet Transform and FFT Methods in the Analysis of EEG Signals
Journal of Medical Systems
Comparison of AR and Welch Methods in Epileptic Seizure Detection
Journal of Medical Systems
Computers in Biology and Medicine
Selection of optimal AR spectral estimation method for EEG signals using Cramer-Rao bound
Computers in Biology and Medicine
Detecting clinically relevant EEG anomalies using discrete wavelet transforms
WAMUS'05 Proceedings of the 5th WSEAS International Conference on Wavelet Analysis and Multirate Systems
Comparison of subspace-based methods with AR parametric methods in epileptic seizure detection
Computers in Biology and Medicine
Study of road surface profile based on maximum entropy methods
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Computer Methods and Programs in Biomedicine
A new HOS-based blind source extraction method to extract µ rhythms from EEG signals
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part II
Detection of Carotid Artery Disease by Using Learning Vector Quantization Neural Network
Journal of Medical Systems
The new method of electroencephalogram representation
Applied Bionics and Biomechanics
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In this study, in order to analyze the EEG signal, the conventional and modern spectral methods were investigated. Interpretation and performance of these methods were detected for clinical applications. For this purpose EEG data obtained from different persons were processed by PC computer using periodogram and AR model algorithms. Periodogram and AR modeling approaches were compared for their resolution and interpretation performance. It was determined that the AR approach is better for the use in clinical and research areas, because of the clear spectra that are obtained by it.