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An efficient feedback canceler for hearing aids based on approximated affine projection

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dc.contributor.authorLee, Sangmin-
dc.contributor.authorKim, Inyoung-
dc.contributor.authorPark, Youngcheol-
dc.date.accessioned2022-12-21T10:51:20Z-
dc.date.available2022-12-21T10:51:20Z-
dc.date.created2022-08-26-
dc.date.issued2006-08-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/181197-
dc.description.abstractIn the feedback cancelation systems in hearing aids, signal cancelation and coloration artifacts can occur for a narrow-band input. In this paper, we propose a new adaptive feedback cancelation algorithm that can achieve fast convergence by approximating the affine projection (AP) algorithm and prevent signal cancelation by controlling the step-size. A Gram-Schmidt prediction error filter (GS-PEF) is used for a stable approximation of the AP algorithm, and the step-size is varied using the prediction factor of the input signal. Simulations results are presented to verify efficiency of the proposed algorithm.-
dc.language영어-
dc.language.isoen-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.titleAn efficient feedback canceler for hearing aids based on approximated affine projection-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Inyoung-
dc.identifier.doi10.1007/11816102_75-
dc.identifier.scopusid2-s2.0-33749580766-
dc.identifier.wosid000240085400075-
dc.identifier.bibliographicCitationCOMPUTATIONAL INTELLIGENCE AND BIOINFORMATICS, PT 3, PROCEEDINGS, v.4115, pp.711 - 720-
dc.relation.isPartOfCOMPUTATIONAL INTELLIGENCE AND BIOINFORMATICS, PT 3, PROCEEDINGS-
dc.citation.titleCOMPUTATIONAL INTELLIGENCE AND BIOINFORMATICS, PT 3, PROCEEDINGS-
dc.citation.volume4115-
dc.citation.startPage711-
dc.citation.endPage720-
dc.type.rimsART-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryBiochemical Research Methods-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.subject.keywordPlusCANCELLATION-
dc.subject.keywordPlusADAPTATION-
dc.identifier.urlhttps://link.springer.com/chapter/10.1007/11816102_75-
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