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dc.contributor.authorLEE, CHen_US
dc.contributor.authorCHEN, LHen_US
dc.date.accessioned2014-12-08T15:03:31Z-
dc.date.available2014-12-08T15:03:31Z-
dc.date.issued1995-02-01en_US
dc.identifier.issn0090-6778en_US
dc.identifier.urihttp://dx.doi.org/10.1109/26.380218en_US
dc.identifier.urihttp://hdl.handle.net/11536/2059-
dc.description.abstractOne of the most serious problems for vector quantization, especially for high dimensional vectors, is the high computational complexity of searching for the closest codeword in the codebook design and encoding phases. Although quantizing high dimensional vectors rather than low dimensional vectors results in better performance, the computation time needed for vector quantization grows exponentially with the vector dimension. This makes high dimensional vectors unsuitable for vector quantization. To overcome this problem, a fast search algorithm, under the assumption that the distortion is measured by the squared Euclidean distance, will be proposed. Using the mean pyramids of codewords, the algorithm can reject many codewords that are impossible matches and hence save a great deal of computation time. The algorithm is efficient for high dimensional codeword searches. Experimental results confirm the effectiveness of the proposed method.en_US
dc.language.isoen_USen_US
dc.titleA FAST SEARCH ALGORITHM FOR VECTOR QUANTIZATION USING MEAN PYRAMIDS OF CODEWORDSen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/26.380218en_US
dc.identifier.journalIEEE TRANSACTIONS ON COMMUNICATIONSen_US
dc.citation.volume43en_US
dc.citation.issue2-4en_US
dc.citation.spage1697en_US
dc.citation.epage1702en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:A1995QV15700066-
dc.citation.woscount61-
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