Prediction of EEG Signal by Digital Filtering
نویسندگان
چکیده
Prediction of EEG signal from past samples is needed for early diagnosis of patients, suffering from frequent epileptic seizure and/or psychotherapeutic treatment of psychiatric patients. This paper compares the performance of various digital filter algorithms to identify the right candidate for application in EEG prediction. The study includes variation of filter order and past sample size, and finally reaffirms the Kalman filter as the solution for its very low RMS prediction error in comparison to LMS, NLMS and RLS filter algorithms.
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