Neuro-Fuzzy Prediction-Based Adaptive Filtering Applied to Severely Distorted Magnetic Field Recordings

This letter presents an adaptive filtering technique, based upon neuro-fuzzy prediction, to enhance magnetic field signal recordings affected by significant anomalies of magnetotelluric origin such as magnetic storms, rain, and cultural noise. A neuro-fuzzy model has been developed and trained to predict the magnetic field signal in the absence of any sizeable disturbances. Thus, at the occurrence of a significant distortion of nonmagnetotelluric origin, the neuro-fuzzy model predicts the healthy magnetic field signal in parallel to the distortion, thereby significantly reducing the latter. Testing the trained system using unseen data verifies the reliability of the model and demonstrates the effectiveness of the neuro-fuzzy prediction-based adaptive filtering method