Faculty Publications

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Author: search.filters.author.Narasimhan, S.V.Subject: search.filters.subject.Active noise control

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    Feedback active noise control based on transform-domain forward-backward LMS predictor
    (Springer London, 2014) Pavithra, S.; Narasimhan, S.V.
    In this paper, a new feedback active noise control (FBANC) system based on the transform-domain forward-backward LMS (TFBLMS) predictor has been proposed. The new ANC system employs the TFBLMS predictor for its main-path (MP) predictor as well as for the noise canceller. To overcome the ill effect of the primary noise field, which acts as an observation noise for the secondary-path (SP) identification, the noise canceller is used. As the main-path predictor is based on the TFBLMS, its convergence rate improves due to its input orthogonalization. Further, its FBLMS nature reduces misadjustment. The use of TFBLMS predictor for noise canceller also gives a good prediction of primary noise at a faster rate, enabling improved SP identification. This improved SP identification indirectly aids the MP predictor to achieve an improved performance. A new filtered-x LMS structure has been proposed to realize the new MP predictor to accommodate the TFBLMS algorithm. The TFBLMS algorithm is applied directly to the noise canceller for SP identification. The proposed new ANC system has been found to have a significantly better noise reduction (by 14.6 dB) over the FBANC system based on tapped delay line time-domain FBLMS algorithm. © 2012 Springer-Verlag London Limited.
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    Steiglitz-McBride adaptive notch filter based on a variable-step-size LMS algorithm and its application to active noise control
    (John Wiley and Sons Ltd Southern Gate Chichester, West Sussex PO19 8SQ, 2016) Roopa, S.; Narasimhan, S.V.; Babloo, B.
    Summary This paper proposes a new Steiglitz-McBride (SM) adaptive notch filter (SM-ANF) based on a robust variable-step-size least-mean-square algorithm and its application to active noise control (ANC). The proposed SM-ANF not only has fast convergence but also has small misadjustment. The variable-step-size algorithm uses the sum of the squared cross correlation between the error signal and the delayed inputs corresponding to the adaptive weights. The cross correlation provides robustness to the broadband signal, which plays the role of noise. The proposed SM-ANF is computationally simpler than the existing Newton/recursive least-squares-type ANF. The frequency response of the new SM-ANF has a notch depth of about -25 dB (for each of the three frequencies considered) and has spectral flatness within 5 dB (peak to peak). This robust notch filter algorithm is used as an observation noise canceller for the secondary path estimation of an ANC system based on the SM method. The ANC with proposed SM-ANF provides not only faster convergence but also an 11-dB improvement in noise attenuation over the SM-based ANC without such a SM-ANF. © © 2015 John Wiley & Sons, Ltd.