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dc.contributor.authorOrdentlich, Or
dc.contributor.authorPolyanskiy, Yury
dc.date.accessioned2020-05-01T20:42:19Z
dc.date.available2020-05-01T20:42:19Z
dc.date.issued2018-06
dc.identifier.isbn978-1-5386-4780-6
dc.identifier.urihttps://hdl.handle.net/1721.1/124986
dc.description.abstractLet Z[superscript n] be iid Bernoulli (δ) and U[superscript n] be uniform on the set of all binary vectors of weight δ[superscript n] (Hamming sphere). As is well known, the entropies of Z[superscript n] and U[superscript n] are within O(√n). However, if X[superscript n] is another binary random variable independent of Z[superscript n] and U[superscript n], we show that H(X[superscript n]+U[superscript n]) and H(X[superscript n]+Z[superscript n]) are within O(√n) and this estimate is tight. The bound is shown via coupling method. Tightness follows from the observation that the channels x[superscript n]⟼x[superscript n]+U[superscript n] and x[superscript n]⟼x[superscript n]+Z[superscript n] have similar capacities, but the former has zero dispersion. Finally, we show that despite the √n slack in general, the Mrs. Gerber Lemma for H(X[superscript n]+U[superscript n]) holds with only an O(log n) correction compared to its brethren for H(X[superscript n]+Z[superscript n]). ©2019 Paper presented at the 2018 IEEE International Symposium on Information Theory (ISIT 2018), June 17-22, 2018, Vail, Colo.en_US
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionof10.1109/ISIT.2018.8437589en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleEntropy under additive Bernoulli and spherical noisesen_US
dc.typeArticleen_US
dc.identifier.citationOrdentlich, Or, and Yury Polyanskiy, "Entropy under additive Bernoulli and spherical noises." 2018 IEEE International Symposium on Information Theory (ISIT 2018) (Piscataway, N.J.: IEEE, 2018): p. 521-25 doi 10.1109/ISIT.2018.8437589 ©2018 Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.relation.journal2018 IEEE International Symposium on Information Theory (ISIT)en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-07-01T17:54:22Z
dspace.date.submission2019-07-01T17:54:23Z
mit.metadata.statusComplete


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