A genetic approach to ARMA filter synthesis for EEG signal simulation

This paper describes the computational simulation of an electroencephalographic (EEG) signal (background activity, alpha waves) by filtering a white noise with an ARMA (Autoregressive Moving Average) filter. The filter coefficients were obtained interactively using genetic algorithms, comparing the spectrum of a real and a simulated signal. Results demonstrate the feasibility of the technique.