Enhanced impulsive noise cancellation based on SSRLS

Impulsive noise is a human made noise and it destroys the information completely. Methods must be investigated to mitigate this noise. In this paper, a State Space Recursive Least Square (SSRLS) algorithm based enhanced adaptive impulsive noise cancellation technique is proposed. Initially the scheme is tested on sinusoidal signal showing fast rate of convergence and excellent tracking performance due to its state space model-dependent recursive parameters. The proposed method came out to be very effective in noise cancellation of signal without requiring reference noise source. The technique is then applied to the Electrocardiogram (ECG) signal, where impulsive noise renders the ECG analysis inaccurate. The convergence characteristics of proposed scheme demonstrated by the simulation results in mean square error (MSE) sense substantiate its effectiveness over some of the existing algorithms.