Prefix Codes for Power Laws with Countable Support

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dc.creatorBaer, Michael B.
dc.date2006-11-15
dc.date2007-06-21
dc.date.accessioned2026-07-07T12:49:25Z
dc.date.available2026-07-07T12:49:25Z
dc.descriptionIn prefix coding over an infinite alphabet, methods that consider specific distributions generally consider those that decline more quickly than a power law (e.g., Golomb coding). Particular power-law distributions, however, model many random variables encountered in practice. For such random variables, compression performance is judged via estimates of expected bits per input symbol. This correspondence introduces a family of prefix codes with an eye towards near-optimal coding of known distributions. Compression performance is precisely estimated for well-known probability distributions using these codes and using previously known prefix codes. One application of these near-optimal codes is an improved representation of rational numbers.
dc.description5 pages, 2 tables, submitted to Transactions on Information Theory
dc.identifierhttps://arxiv.org/abs/cs/0611073
dc.identifierhttp://arxiv.org/abs/cs/0611073
dc.identifierInformation Theory, 2008. ISIT 2008. IEEE International Symposium on
dc.identifierdoi:10.1109/ISIT.2008.4595434
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/222396
dc.subjectInformation Theory
dc.subjectE.4; H.1.1; I.2.8
dc.titlePrefix Codes for Power Laws with Countable Support
dc.typetext

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