A recursive least M-estimate (RLM) adaptive filter for robust filtering inimpulse noise

This paper proposes a recursive least M-estimate (RLM) algorithm for robust adaptive filtering in impulse noise, It employs an M-estimate cost functio n, which is able to suppress the effect of impulses on the filter weights, Simulation results showed that the RLM algorithm performs better than the c onventional RLS, NRLS, and the OSFKF algorithms when the desired and input signals are corrupted by impulses. Its initial convergence, steady-state er ror, computational complexity, and robustness to sudden system change are c omparable to the conventional RLS algorithm in the presence of Gaussian noi se alone.