Fast convergence transversal adaptive filtering algorithm for impulsive environment based on T distribution assumption

In this paper we propose an adaptive filter based on assumption that the error is t-distributed with X degree of freedom, The optimal system is updated by using the LMS-like algorithm. When the input is impulsive signals, the convergence of the algorithm with small X is faster than when large X is used. Simulation results also show that the convergence of the proposed method is faster than other LMS-variant that has been earlier proposed.