Prefix Codes for Power Laws with Countable Support

Details Prefix Codes for Power Laws with Countable Support Prefix Codes for Power Laws with Countable Support

2006-11-15

arxiv.org/abs/cs/0611073v2

Information Theory, 2008. ISIT 2008. IEEE International Symposium on

Computer Science

Information Theory

5 pages, 2 tables, submitted to Transactions on Information Theory

Scientific paper

10.1109/ISIT.2008.4595434

In 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.

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