Optimal parsing trees for run-length coding of biased data

Sharon Aviran, Paul H. Siegel, Jack K. Wolf

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We study coding schemes which encode unconstrained sequences into run-length-limited (d, k)-constrained sequences. We present a general framework for the construction of such (d, k)-codes from variable-length source codes. This frame-work is an extension of the previously suggested bit stuffing, bit flipping and symbol sliding algorithms. We show that it gives rise to new code constructions which achieve improved performance over the three aforementioned algorithms. Therefore, we are interested in finding optimal codes under this framework, optimal in the sense of maximal achievable asymptotic rates. However, this appears to be a difficult problem. In an attempt to solve it, we are led to consider the encoding of unconstrained sequences of independent but biased (as opposed to equiprobable) bits. Here, our main result is that one can use the Tunstall source coding algorithm to generate optimal codes for a partial class of (d, k) constraints.

Original languageEnglish (US)
Title of host publicationProceedings - 2006 IEEE International Symposium on Information Theory, ISIT 2006
Pages1495-1499
Number of pages5
DOIs
StatePublished - Dec 1 2006
Event2006 IEEE International Symposium on Information Theory, ISIT 2006 - Seattle, WA, United States
Duration: Jul 9 2006Jul 14 2006

Other

Other2006 IEEE International Symposium on Information Theory, ISIT 2006
CountryUnited States
CitySeattle, WA
Period7/9/067/14/06

Fingerprint

Run Length
Parsing
Biased
Optimal Codes
Coding
Source Coding
Encoding
Partial
Framework

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

Cite this

Aviran, S., Siegel, P. H., & Wolf, J. K. (2006). Optimal parsing trees for run-length coding of biased data. In Proceedings - 2006 IEEE International Symposium on Information Theory, ISIT 2006 (pp. 1495-1499). [4036216] https://doi.org/10.1109/ISIT.2006.262117

Optimal parsing trees for run-length coding of biased data. / Aviran, Sharon; Siegel, Paul H.; Wolf, Jack K.

Proceedings - 2006 IEEE International Symposium on Information Theory, ISIT 2006. 2006. p. 1495-1499 4036216.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Aviran, S, Siegel, PH & Wolf, JK 2006, Optimal parsing trees for run-length coding of biased data. in Proceedings - 2006 IEEE International Symposium on Information Theory, ISIT 2006., 4036216, pp. 1495-1499, 2006 IEEE International Symposium on Information Theory, ISIT 2006, Seattle, WA, United States, 7/9/06. https://doi.org/10.1109/ISIT.2006.262117
Aviran S, Siegel PH, Wolf JK. Optimal parsing trees for run-length coding of biased data. In Proceedings - 2006 IEEE International Symposium on Information Theory, ISIT 2006. 2006. p. 1495-1499. 4036216 https://doi.org/10.1109/ISIT.2006.262117
Aviran, Sharon ; Siegel, Paul H. ; Wolf, Jack K. / Optimal parsing trees for run-length coding of biased data. Proceedings - 2006 IEEE International Symposium on Information Theory, ISIT 2006. 2006. pp. 1495-1499
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