Bias-compensated FX-LMS algorithm

• Published in: Electronics letters Vol. 56; no. 24; pp. 1340 - 1343
• Main Authors: da Silva, L.P.R, de Souza, J.V.G, Colares, J, de Lima, A.A, Haddad, D.B
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 26.11.2020
• Subjects: acoustic signal processing; active noise control; adaptive filter; adaptive filters; additive noise; bias‐compensated FX‐LMS algorithm; excitation data; expanding field; first‐order stochastic analysis; input signal; least mean squares methods; noise cancelling; noise perturbations; numerical stability; secondary perturbations; Signal processing; standard filtered‐x least mean squares; standard FX‐LMS algorithm; stochastic processes; least mean squares methods; secondary perturbations; adaptive filters; active noise control; noise perturbations; first-order stochastic analysis; excitation data; standard filtered-x least mean squares; numerical stability; input signal; adaptive filter; additive noise; bias-compensated FX-LMS algorithm; noise cancelling; stochastic processes; acoustic signal processing; standard FX-LMS algorithm; expanding field
• ISSN: 0013-5194; 1350-911X; 1350-911X
• DOI: 10.1049/el.2020.2010

Active noise control is an expanding field that requires a suitable synthesis of secondary perturbations. Unfortunately, most schemes for noise cancelling do not take into account that the input signal that drives the adaptive filter can be noisy. In this Letter, it is theoretically shown that noise perturbations in the excitation data degrade the performance of the standard filtered-x least mean squares (FX-LMS) algorithm. Furthermore, a method that compensates such an issue is devised, and a first-order stochastic analysis of the resulting algorithm is performed. The results reveal that the proposed scheme outperforms the standard FX-LMS algorithm, even when the variance of the additive noise in the input is not accurately estimated.