Estimation of electrooculography (EOG) and blinking signals could be done by using numerous algorithms. The separation of EOG and blinking signals is hard if the blinking pulses occur in the neighborhood of saccades. The appropriate estimation and signals separation could be obtained by using the optimization algorithm and a proper signals model. The proposed method improves the convergence of evolution–based technique and reduces the optimization time by using the additional algorithm for the estimation of possible positions of blinking pulses, the saccades positions and the EOG levels. A median filter based estimator is used for the initialization of optimization algorithm of blinking pulses. A differential filter based detector is used for the initialization of saccades position and the EOG signal level values between them. The proposed method reduces the computation time a few times what is important for the possibility of real–time implementation.