  An improved proportionate adaptive filter based on the Maximum Correntropy
Criterion (IP-MCC) is proposed for identifying the system with variable
sparsity in an impulsive noise environment. Utilization of MCC mitigates the
effect of impulse noise while the improved proportionate concepts exploit the
underlying system sparsity to improve the convergence rate. Performance
analysis of the proposed IP-MCC is carried out in the steady state and our
analysis reveals that the steady state Excess Mean Square Error (EMSE) of the
proposed IP-MCC filter is similar to the MCC filter. The proposed IP-MCC
algorithm outperforms the state of the art algorithms and requires much less
computational effort. The claims made are validated through exhaustive
simulation studies using the correlated input.
