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dc.contributor.authorSo, Stephenen_US
dc.contributor.authorPaliwal, Kuldipen_US
dc.contributor.editorM. Rangaswamy, F.J. Harrisen_US
dc.date.accessioned2017-04-24T10:06:42Z
dc.date.available2017-04-24T10:06:42Z
dc.date.issued2007en_US
dc.date.modified2009-09-21T05:49:26Z
dc.identifier.issn10512004en_US
dc.identifier.doi10.1016/j.dsp.2005.08.005en_AU
dc.identifier.urihttp://hdl.handle.net/10072/17263
dc.description.abstractIn this article, we ?rst review the vector quantiser and discuss its well-known advantages over the scalar quantiser, namely the space-?lling advantage, the shape advantage, and the memory advantage. It is important to understand why vector quantisers always perform better than any other quantisation scheme for a given dimension, as this will provide the basis for our investigation on improving product code vector quantisers which, despite having much lower computational and memory requirements, result in suboptimal quantisation performance. The main focus is on improving the ef?ciency of the split vector quantiser (SVQ), in terms of computational complexity and rate-distortion performance. Though SVQ has lower computational and memory requirements than those of the unconstrained vector quantiser, the vector splitting process adds numerous constraints to the codebook, which results in suboptimal quantisation performance. Speci?cally, the reduced dimensionality affects all three vector quantiser advantages. Therefore, we investigate a new type of hybrid vector quantiser, called the switched split vector quantiser (SSVQ), that addresses the memory and shape suboptimality of SVQ, leading to better quantisation performance. In addition, the SSVQ has lower computational complexity than the SVQ, at the expense of higher memory requirements for storing the codebooks. We evaluate the performance of SSVQ in LPC parameter quantisation, used in narrowband CELP speech coders, and compare it against other quantisation schemes.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherElsevieren_US
dc.publisher.placeNetherlandsen_US
dc.publisher.urihttp://www.elsevier.com/wps/find/journaldescription.cws_home/622818/description#descriptionen_AU
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofpagefrom138en_US
dc.relation.ispartofpageto171en_US
dc.relation.ispartofjournalDigital Signal Processingen_US
dc.relation.ispartofvolume17en_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchcode280204en_US
dc.titleEfficient product code vector quantisation using the switched split vector quantiseren_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.facultyGriffith Sciences, Griffith School of Engineeringen_US
gro.date.issued2007
gro.hasfulltextNo Full Text


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