Abstract
The paper describes the method for electroencephalogram (EEG) analysis based on the stochastic resonance (SR) effect. The numerical computation has provided the separation of low frequency components that fall within the δ-rhythm band. This is currently central in the neuropathology diagnostics, because the presence of low frequencies in the EEG is abnormal and bears witness to the disease. For verification, the data obtained with the use of the SR effect have been compared with the computations based on the autocorrelation function (ACF) processing. The comparison has shown their good agreement.
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