A new variable step-size normalized subband adaptive filter algorithm employing dynamic selection of subband filters

This paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm with dynamic selection (DS) of subband filters. The selection strategy is performed to achieve the largest decrease between the successive mean square deviations at every iteration. The proposed VSS-DS-NSAF has fast convergence speed and low steady-state mean square error (MSE). Also due to DS feature, the VSS-DS-NSAF has lower computational complexity than VSS-NSAF. We demonstrate the good performance of the proposed algorithm through several simulations in system identification scenario.