GVFF-RLS Adaptive Algorithm for Elimination of Ocular Artifacts from EEG Signals

In this paper, we have implemented Gradient Variable Forgetting Factor (GVFF) algorithm through Recursive Least Squares (RLS) method as a noise canceller for elimination of ocular artifacts from raw Electroencephalogram (EEG) signals under dynamic environment. We have recorded two reference signals such as vertical eye movements and horizontal eye movements separately. These recorded signals are processed through finite impulse response filter, whose coefficients are updated recursively using GVFF-RLS algorithm for obtaining clean EEG signals by subtraction process. Our proposed method shows least mean square error in comparison with conventional techniques.