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Parametric Modeling of EEG by Mono-Component Non-Stationary Signal

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Document pages: 28 pages

Abstract: In this paper, we propose a novel approach for parametric modeling ofelectroencephalographic (EEG) signals. It is demonstrated that the EEG signalis a mono-component non-stationary signal whose amplitude and phase (frequency)can be expressed as functions of time. We present detailed strategy forestimation of the parameters of the proposed model with high accuracy.Simulation study illustrates the procedure of model fitting. Someinterpretation of the characteristic features of the model is described.

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