Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/142538
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dc.contributor.authorWen, Shulinen_US
dc.contributor.authorGan, Woon-Sengen_US
dc.contributor.authorShi, Dongyuanen_US
dc.date.accessioned2020-06-24T02:43:34Z-
dc.date.available2020-06-24T02:43:34Z-
dc.date.issued2020-
dc.identifier.citationWen, S., Gan, W.-S., & Shi, D. (2020). Using empirical wavelet transform to speed up selective filtered active noise control system. The Journal of the Acoustical Society of America, 147(5), 3490–3501. doi:10.1121/10.0001220en_US
dc.identifier.issn0001-4966en_US
dc.identifier.urihttps://hdl.handle.net/10356/142538-
dc.description.abstractThe gradual adaptation and possibility of divergence hinder the active noise control system from being applied to a wider range of applications. Selective active noise control has been proposed to rapidly reduce noise by selecting a pre-trained control filter for different primary noise detected without an error microphone. For stationary noise, considerable noise reduction performance with a short selection period is obtained. For non-stationary noise, more restrictive requirements are imposed on instant convergence, as it leads to faster tracking and better noise reduction performance. To speed up a selective filtered active noise control system, empirical wavelet transform is introduced here to accurately and instantaneously extract the frequency information of primary noise. The boundary of the first intrinsic mode function of random noises is extracted as the instant signal feature. Primary noise is attenuated immediately by picking the optimal pre-trained control filter labeled by the nearest boundary. The storage requirement for a pre-trained control filter library is reduced. Instant control is obtained, and the instability caused by output saturation is overcome. With more concentrated energy distribution, better noise reduction performance is achieved by the proposed algorithm compared to conventional and selective active noise control algorithms. Simulation results validate these advantages of the proposed algorithm.en_US
dc.description.sponsorshipNRF (Natl Research Foundation, S’pore)en_US
dc.language.isoenen_US
dc.relationCOT-V4-2019-1en_US
dc.relation.ispartofThe Journal of the Acoustical Society of Americaen_US
dc.rights© 2020 Acoustical Society of America. All rights reserved. This paper was published in The Journal of the Acoustical Society of America and is made available with permission of Acoustical Society of America.en_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleUsing empirical wavelet transform to speed up selective filtered active noise control systemen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.contributor.organizationDigital Signal Processing Laben_US
dc.identifier.doi10.1121/10.0001220-
dc.description.versionPublished versionen_US
dc.identifier.issue5en_US
dc.identifier.volume147en_US
dc.identifier.spage3490en_US
dc.identifier.epage3501en_US
dc.subject.keywordsMicrophonesen_US
dc.subject.keywordsWavelet Transformen_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
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