  Multichannel active noise control (MCANC) is widely utilized to achieve
significant noise cancellation area in the complicated acoustic field.
Meanwhile, the filter-x least mean square (FxLMS) algorithm gradually becomes
the benchmark solution for the implementation of MCANC due to its low
computational complexity. However, its slow convergence speed more or less
undermines the performance of dealing with quickly varying disturbances, such
as piling noise. Furthermore, the noise power variation also deteriorates the
robustness of the algorithm when it adopts the fixed step size. To solve these
issues, we integrated the normalized multichannel FxLMS with the momentum
method, which hence, effectively avoids the interference of the primary noise
power and accelerates the convergence of the algorithm. To validate its
effectiveness, we deployed this algorithm in a multichannel noise control
window to control the real machine noise.
