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dc.contributor.authorKostina, Victoria
dc.contributor.authorPolyanskiy, Yury
dc.contributor.authorVerdu, Sergio
dc.date.accessioned2019-07-23T20:11:58Z
dc.date.available2019-07-23T20:11:58Z
dc.date.issued2015-08
dc.date.submitted2015-10
dc.identifier.issn0018-9448
dc.identifier.issn1557-9654
dc.identifier.urihttps://hdl.handle.net/1721.1/121939
dc.description.abstractThis paper studies the fundamental limits of the minimum average length of lossless and lossy variable-length compression, allowing a nonzero error probability ε, for lossless compression. We give nonasymptotic bounds on the minimum average length in terms of Erokhin's rate-distortion function and we use those bounds to obtain a Gaussian approximation on the speed of approach to the limit, which is quite accurate for all but small blocklengths: (1 - ε) k H(S) - ((V(S)/2π))1/2 exp[-((Q-1 (ε))2/2)], where Q-1(·) is the functional inverse of the standard Gaussian complementary cumulative distribution function, and V(S) is the source dispersion. A nonzero error probability thus not only reduces the asymptotically achievable rate by a factor of 1 - ε, but this asymptotic limit is approached from below, i.e., larger source dispersions and shorter blocklengths are beneficial. Variable-length lossy compression under an excess distortion constraint is shown to exhibit similar properties.en_US
dc.description.sponsorshipNational Science Foundation (U.S.). Center for Science of Information (Grant CCF-0939370)en_US
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionof10.1109/tit.2015.2438831en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleVariable-Length Compression Allowing Errorsen_US
dc.typeArticleen_US
dc.identifier.citationKostina, Victoria, Yury Polyanskiy and Sergio Verdú. "Variable-Length Compression Allowing Errors." IEEE Transactions on Information Theory 61, no. 8 (August 2015): pp. 4316-4330.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Laboratory for Information and Decision Systemsen_US
dc.relation.journalIEEE Transactions on Information Theoryen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2019-07-01T16:42:13Z
dspace.date.submission2019-07-01T16:42:14Z
mit.journal.volume61en_US
mit.journal.issue8en_US


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