Improved performance of impulse active noise control using active function threshold with absolute harmonic variable step-size algorithm

The Standard (conventional) adaptive algorithms exhibits low convergence rate and minimum noise suppression, or else the system becomes unstable under Gaussian and non-Gaussian (impulsive noise S alpha S distributions) noise environments. In order to overcome the drawback of traditional algorithms (i.e., to eliminate unwanted noise), the popular algorithm Filtered Cross Minimum Square (FxLMS) is used in Active Noise Control (ANC), not only to improve its efficiency but also to improve its performance. In this paper, we proposed two improvements: first, we proposed a novel method Active threshold function FxLMS (ATFxLMS) being employed in ANC in the paths of primary (reference) and error signals; a second proposal is employing the Variable Step-Size based on Absolute Harmonic Mean (AHMVSS) of error signal. The idea behind this method is that the step-size of the algorithm varies depending on the harmonic mean of error signal obtained from the error location. In comparison to the fixed step-size algorithm, the proposed ATF-AHMVSS provided an improved convergence rate for the desired ANC efficiency. Moreover computational complication of the proposed method was examined as it was found that the proposed algorithm provided stable condition for ANC systems. Computer simulation results are revealed that the proposed (AT & AHMVSS-FxLMS) algorithm have attained excellent performance in terms of convergence speed, noise reduction and minimum steady state error as compared to other existing algorithms under different noise inputs. The results obtained from the proposed algorithm show outperformance compared to traditional adaptive algorithms. (c) 2020 Elsevier B.V. All rights reserved.