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Adaptive Tap-Length Based Sub-band Mean M-Estimate Filtering for Active Noise Cancellation

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Abstract

Electronic equipment used on a daily basis now frequently includes active noise cancellation. The adaptive filters, which are positioned within, are essential for noise cancellation. An essential component to take into account for the overall performance is the structural and computational complexity of the filter. The filter’s structure has an impact on this. The amount of taps determines the structure. Active noise cancellation filters often have set tap lengths and are lengthy, which causes sluggish convergence and delay. As a result, a trade-off between the filter’s length and convergence is required. This is conceivable if there is a flexible filter with a tap length that adapts to the environment while still ensuring acceptable convergence. This study proposes a novel Minimum Mean M-estimate method with changeable tap length and uses a sub-band adaptive filtering technique to shorten the filter’s length. In order to maximize the filter’s efficiency, the advantages of three approaches are specifically merged in this work. They are the proposed algorithm, the proposed method’s variable tap length variant, and the sub-band adaptive filtering. The simulation’s findings and recommendations are supported.

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Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Dr B R Ambedkar National Institute of Technology, Jalandhar, Punjab, 144008, India

    Asutosh Kar

  2. Center for Advanced Data Science, Vellore Institute of Technology, Chennai, 600127, India

    S. Shoba

  3. Department of Electronic Systems, Aalborg University, Aalborg, 9000, Denmark

    Srikanth Burra

  4. Department of Electronics and Communication Engineering, Ajay Kumar Garg Engineering College, Ghaziabad, 201009, India

    Pankaj Goel

  5. Department of Electronics and Communication Engineering, Sarala Birla University Ranchi, Jharkand, 834002, India

    Sanjeev Kumar

  6. Department of Electronics and Communication Engineering, National Institute of Technology, Warangal, Telangana, 506004, India

    Vasundhara

  7. Faculty of Technical Sciences in Cacak, University of Kragujevac, Kragujevac, Serbia

    Vladimir Mladenovic

  8. Department of Robotics and AI, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand

    Pitikhate Sooraksa

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  1. Asutosh Kar
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Correspondence to Asutosh Kar.

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Kar, A., Shoba, S., Burra, S. et al. Adaptive Tap-Length Based Sub-band Mean M-Estimate Filtering for Active Noise Cancellation. Circuits Syst Signal Process 43, 5912–5932 (2024). https://doi.org/10.1007/s00034-024-02731-0

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