Filtered-X $q$-Gradient Least Mean Mixed-Norm Algorithm for Active Noise Control

On the basis of the notion of Jackson derivative, the filtered-x q-gradient least mean mixed-norm algorithm (FxqLMMN) is proposed for active noise control by using q-gradient to minimize the cost function. To reconcile the balance between errors in steady-state and convergence speed, an additional time-varying q-parameter is introduced in the proposed algorithm. Simulation consequences exhibit that, compared to prior algorithms, the proposed algorithm speeds up convergence and provides excellent noise suppression effects under a diversity of common noise input environments.