A modified active noise control algorithm for convex combined structures based on partial updating of weight matrices

Convex combination schemes with fast tracking ability and good steady-state restoration performance have attracted wide attention in Active Noise Control (ANC) systems. The scheme can combine the outputs of multiple filters. However, the time domain filter-X least mean square (FxLMS) algorithm used in traditional convex combination structure has the problem of high computational complexity. Compared with the conventional FxLMS algorithm, the time–frequency domain FxLMS (TF-FxLMS) algorithm can compute gradient estimates and filter reference signals in the frequency domain to reduce the computation. Since the algorithm is a block processing of the signal in the frequency domain, the presence of the fast fourier transform (FFT) introduces unwanted delays which causes the rate of convergence to slow down. FFT operations should be performed at a sampling interval, which limits the real-time implementation of the algorithm. In order to reduce the computational complexity of traditional convex combination and improve the performance of the algorithm, a convex combined structure algorithm of normalized filter-X least mean square (NFxLMS) algorithm and TF-FxLMS algorithm is proposed in this paper. In addition, in order to further reduce the amount of computation, the NFxLMS algorithm is decomposed into NFxLMS algorithm and TF-FxLMS algorithm by means of partial updating of weight matrix. In this paper, the computational complexity of the proposed algorithm is analyzed and compared with the traditional algorithm. The simulation results show that the proposed algorithm has better noise reduction effect than the traditional algorithm under the noise input conditions of various driving conditions. At the same time, it has the advantage of lower computational complexity.