SSLMS Algorithm Based Impulsive Noise Cancellation from ECG Signal

A State Space Least Mean Square (SSLMS) algorithm based technique for impulsive noise cancellation from Electrocardiogram (ECG) signal is proposed. For removal of noise from any system, the input signal, which is correlated version of noise in this case, may not necessarily present. So an algorithm that does not require any input signal must also be investigated. As the presented technique is incorporating an unforced linear time-varying state space model, it does not involve any input signal and shows better noise cancellation potential as compared to Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) adaptive algorithms. Simulation results indicate that the suggested technique has faster convergence and better tracking capability as compared to the reported algorithms hence proving it to be an effective solution for elimination of impulsive noise.