A switching strategy of the frequency-domain adaptive algorithm for active noise control

The bin-normalized frequency domain block least mean square (NFBLMS) algorithm is a good choice in the active noise control system due to its benefit of high convergence speed. However, it suffers from a biased steady-state solution with insufficient adaptive filter length, often unavoidable due to the influence of the secondary path. A modified frequency domain block least mean square (MFBLMS) algorithm with guaranteed optimal steady-state performance has been proposed recently. However, its convergence speed is generally lower than that of the NFBLMS algorithm. In this paper, a mixed algorithm combining the NFBLMS and MFBLMS algorithms is proposed based on the analysis of the initial convergence trajectory of the NFBLMS algorithm. An effective switching strategy is designed, enabling the MFBLMS algorithm after the NFBLMS algorithm approaches its steady state and shifting back to the NFBLMS algorithm when the change of environment is detected. The mixed algorithm has both the high convergence speed and the optimal steady-state performance, and its effectiveness is validated by simulations using measured acoustic transfer functions.