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Index assignment in vector quantisation for channels with memory

dc.citation.epage167en_US
dc.citation.issue3en_US
dc.citation.spage162en_US
dc.citation.volume149en_US
dc.citation.woscount0
dc.contributor.authorChang, WWen_US
dc.contributor.authorHsu, HIen_US
dc.contributor.department電信工程研究所zh_TW
dc.contributor.departmentInstitute of Communications Engineeringen_US
dc.date.accessioned2014-12-08T15:42:21Z
dc.date.available2014-12-08T15:42:21Z
dc.date.issued2002-06-01en_US
dc.description.abstractThe study presents a formulation of a Hadamard framework for analysing the vector quantisation over channels with memory. In seeking faster response, classes of index assignments are defined in terms of the Hadamard transform of channel transition probabilities. An index assignment algorithm is developed that achieves high robustness against channel errors, and its performance in vector quantisation of Gauss-Markov sources under noisy channel conditions is illustrated.en_US
dc.identifier.doi10.1049/ip-vis:20020366en_US
dc.identifier.issn1350-245Xen_US
dc.identifier.journalIEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSINGen_US
dc.identifier.urihttp://dx.doi.org/10.1049/ip-vis:20020366en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/28759
dc.identifier.wosnumberWOS:000177714500005
dc.language.isoen_USen_US
dc.titleIndex assignment in vector quantisation for channels with memoryen_US
dc.typeArticleen_US

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