It is very important in remote cardiac diagnosis to extract pure ECG signal
from the contaminated recordings of the signal. When recording the ECG
signal in the laboratory, the signal is affected by numerous artifacts. Varies
artifacts generally degrades the signal quality are PLI, EM, MA and EM.
In addition to these, the channel noise also added when transmitting signal
from remote location to diagnosis center for analyzing the signal. There are
several approaches are used to reduce the noise present in the ECG signal.
From the literature it is proven that compared to non adaptive filters, adaptive
filters play vital role to trace the random changes in the corrupted signals.
In this paper, we proposed efficient Variable step size leaky least mean
fourth algorithm and its sign versions for reducing the complexity. These
algorithms shows that it gives low steady state error due to least mean fourth
and fast convergence rate that is it tracks the input signal quickly because of
its variable step size is high at initial iterations of signal compared to the
LMS algorithm. The performance of the algorithm is evaluated using SNR,
frequency spectrum, MSE, misadjustment and convergence characteristics. 

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