Entropy and Data Compression Schemes

IEEE Transactions on Information Theory

Volumn 39, Issue 1, 1993, Pages 78-83

  Weiss, Benjamin ^b  

^a STANFORD UNIVERSITY   (United States)

^b HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

data compression; Entropy; Shannon MeMillan theorem

Indexed keywords

ENTROPY; INFORMATION THEORY; PROBABILITY;

ERGODIC PROCESS; LEMPEL-ZIV PARSING; SHANNON-MCMILLAN THEOREM;

DATA COMPRESSION;

EID: 0027266419     PISSN: 00189448     EISSN: 15579654     Source Type: Journal    
DOI: 10.1109/18.179344     Document Type: Article

References (7)

1. A. Lempel and J. Ziv, “Compression of individual sequences via variable rate coding,” IEEE Trans. Inform. Theory, vol. IT-24, pp. 530-536, 1978.
2. —, “A universal algorithm for sequential data compression,” IEEE Trans. Inform. Theory, vol. IT-23, pp. 337–343, 1977.
3. D. Ornstein and B. Weiss, “The Shannon-McMillan-Breiman theorem for a class of amenable groups,” Israel J. of Math., vol. 44, pp. 53–60, 1983.
4. —, “Entropy and isomorphism theorems for actions of amenable groups,” J. d’Analyse Math., vol. 48, pp. 1–141, 1987.
5. —, “How sampling reveals a process,” Ann. Probab. Theory, vol. 18, pp. 905–930, 1990.
6. A. Wyner and J. Ziv, “Some asymptotic properties of the entropy of a stationary ergodic data source with applications to data compression,” IEEE Trans. Inform. Theory, vol. 35, pp. 1250–1258, Nov. 1989.
7. J. Ziv, “Coding theorems for individual sequences,” IEEE Trans. Inform. Theory, vol. IT-24, pp. 405–412, 1978.