An Active Noise Control Algorithm Using Variable Step Size Adaptive Filter with Constraint in Sparse System

This paper proposes an active noise control (ANC) algorithm that enable to use in a sparse system environment, An adaptive filter, which is one of the methods for estimating the inverse channel, was used to perform active noise control. The filtered-x algorithm was employed through the adaptive filter to address the issue of secondary path distortion in active noise control. For estimating the inverse channels in the sparse system, the
$l_{0}$
-norm was employed, and a newly analyzed mean square deviation (MSD) was applied to calculate the optimal step size that enhance convergence performance. The modified reset algorithm was also applied to ensure that the adaptive filter can track the inverse channel properly even in situations where the system suddenly changes, Various simulations show that the proposed ANC algorithm has better convergence performance than the other algorithms that used in sparse system, In addition, the tracking performance in system sudden change situation shows that the proposed algorithm estimates the inverse channel properly.