A performance optimized algorithm for NANC systems

In view of the convergence of narrowband active noise control (NANC) algorithm, a novel adaptive filtered-X weighted accumulated least-mean-square algorithm termed variable forgetting-factor and variable step-size (VFVS-FXWALMS) is proposed for NANC systems. On the basis of FXWALMS algorithm, a scheme using variable forgetting-factor and variable step-size is proposed to obtain better step-size and forgetting-factor values, which can not only better solve the contradiction among convergence, tracking capabilities and steady-state error of the algorithm, but also enhance the anti-interference capability of the system. Thus, the proposed algorithm improves considerably the overall performance of the system. Computer simulations are conducted to demonstrate the superior performance of the proposed algorithm in both stationary and non-stationary scenarios.