Adaptive scheme for elimination of broadband noise and impulsive disturbances from AR and ARMA signals

The problem of elimination of measurement noise and impulsive disturbances from autoregressive and autoregressive moving average signals is considered. It is shown that the task of simultaneous detection/tracking/restoration can be stated as a nonlinear filtering problem and solved using the theory of extended Kalman filter. Numerical tests carried out for real audio signals corrupted by both real and artificially generated disturbances confirm very good properties of the proposed algorithm.