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Low Complexity Sequential Lossless Coding for Piecewise Stationary Memoryless Sources (1999)  (Make Corrections)  (8 citations)
Gil I. Shamir, Neri Merhav



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Abstract: Three strongly sequential, lossless compression schemes, one with linearly growing per-letter computational complexity, and two with fixed per-letter complexity, are presented and analyzed for memoryless sources with abruptly changing statistics. The first method, which improves on Willems' weighting approach, asymptotically achieves a lower bound on the redundancy, and hence is optimal. The second scheme achieves redundancy of O (log N=N) when the transitions in the statistics are large,... (Update)

Context of citations to this paper:   More

...of non stationary sources. One example of such a class is that of memoryless sources with piecewise xed letter probabilities [8] 9] [16] [17] 19] 20] namely, sources for which the probability mass function (PMF) is subjected to occasional abrupt changes. This model...

...non stationary sources. One example of such a class is that of memoryless sources with piecewise xed letter probabilities [8] 9] 16] [17], 19] 20] namely, sources for which the probability mass function (PMF) is subjected to occasional abrupt changes. This model and its...

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BibTeX entry:   (Update)

G. I. Shamir and N. Merhav, \Low complexity sequential lossless coding for piecewise stationary memoryless sources," to appear in the July 1999 issue of IEEE Trans. Inform. Theory . http://citeseer.ist.psu.edu/shamir99low.html   More

@misc{ shamir99low,
  author = "G. Shamir and N. Merhav",
  title = "Low complexity sequential lossless coding for piecewise stationary memoryless
    sources",
  text = "G. I. Shamir and N. Merhav, \Low complexity sequential lossless coding
    for piecewise stationary memoryless sources, to appear in the July 1999
    issue of IEEE Trans. Inform. Theory .",
  year = "1999",
  url = "citeseer.ist.psu.edu/shamir99low.html" }
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2319   Elements of Information Theory (context) - Cover, Thomas - 1991
458   A universal algorithm for sequential data compression - Ziv, Lempel - 1977
293   Compression of individual sequences via variable-rate coding - Ziv, Lempel - 1978
163   Principles and Practice of Information Theory (context) - Blahut - 1991
91   The Context-Tree weighting method: basic properties - Willems, Shtarkov et al. - 1995
78   Universal coding, information, prediction, and estimation (context) - Rissanen - 1984
68   Entropy and Information Theory - Gray - 1990
66   Information Theory: Coding Theorems for Discrete Memoryless .. (context) - Csiszar, Korner - 1981
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41   The performance of universal encoding (context) - Krichevsky, Trofimov - 1981
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34   A strong version of the redundancy-capacity theorem of unive.. (context) - Merhav, Feder - 1995
27   Arithmetic coding for data compression - Howard, Vitter - 1994
15   Probabilistic Information Theory (context) - Jelinek - 1968
15   The sliding-window Lempel-Ziv algorithm is asymptotically op.. (context) - Wyner, Ziv - 1994
13   Coding for a binary Independent Piecewise-Identically-Distri.. (context) - Willems - 1996
13   Asymptotically Optimal Classification for Multiple Tests wit.. (context) - Gutman - 1989
8   Multi-alphabet universal coding of memoryless sources (context) - Shtarkov, Tjalkens et al. - 1995
7   On classification with empirically observed statistics and u.. (context) - Ziv - 1988
5   the minimum description length principle for sources with pi.. (context) - Merhav - 1993
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2   An improvement of dynamic Huffman coding with a simple repet.. (context) - Yokoo - 1991
2   Weighted coding methods for binary piecewise memoryless sour.. (context) - Willems, Casadei - 1995
2   Live-and-die coding for binary piecewise i.i.d. sources (context) - Willems, Krom - 1997



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