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

dc.contributor.authorKar, Asutosh
dc.contributor.authorShoba, S.
dc.contributor.authorBurra, Srikanth
dc.contributor.authorGoel, Pankaj
dc.contributor.authorKumar, Sanjeev
dc.contributor.authorVasundhara
dc.contributor.authorMladenovic, Vladimir
dc.contributor.authorSooraksa, Pitikhate
dc.date.accessioned2026-08-06T10:47:00Z
dc.date.available2026-08-06T10:47:00Z
dc.date.issued2024-09-01
dc.description.abstractElectronic 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.
dc.identifier.citationCircuits Systems and Signal Processing, 43(9), 5912-5932, 2024
dc.identifier.doi10.1007/s00034-024-02731-0
dc.identifier.issn0278081X
dc.identifier.other2-s2.0-85195443691
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/15879
dc.sourceCircuits Systems and Signal Processing
dc.subjectActive noise cancellation (ANC)
dc.subjectAdaptive filters
dc.subjectFiltered-X least mean square algorithm
dc.subjectFractional tap-length
dc.subjectSub-band adaptive filtering
dc.titleAdaptive Tap-Length Based Sub-band Mean M-Estimate Filtering for Active Noise Cancellation
dc.typeArticle

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