An Adaptive Momentum Driven Variable Step-Size Filtered-X Weight Accumulated LMS for Improved HNANC

In the scope of this paper, a group of adaptive algorithms with variable step size (VSS) is designed specifically for a hybrid narrow-band active noise control (HNANC) system. Traditional least mean squares (LMS) algorithms often face challenges in dynamic noise environments due to their fixed step size and slow convergence rates. To overcome these limitations, both the momentum variable step size filtered-x weight accumulated LMS algorithm and the VSS filtered-x LMS algorithm are presented as potential solutions to enhance precision and stability in an environment with numerous noise effects. The proposed approach utilizes VSS, which derives from the varying momentum factor of the variable. Additionally, it integrates these two factors to drive the weight accumulated least mean square technique for an HNANC system. The results of the simulation validate the enhancement in noise mitigation and its practical application, particularly in devices requiring high adaptability and performance, such as hearing aids and headphones that restrict background noise, which can be accomplished using the proposed algorithms in comparison to their existing alternatives.