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Part of the book series: Mathematics and Its Applications ((MAIA,volume 274))

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Abstract

A universal code is suited for many sources simultaneously. To develop such a code we need only calculate the capacity of a communication channel. Universal codes are constructed explicitly for some interesting sets of sources. Those are Bernoulli, Markov, monotone sources (probabilities of letters are ordered). There are both blockto-variable-length and variable-length-to-block universal codes. There is a sequence of codes, which is weakly universal on the set of all stationary sources (the redundancy goes to zero).

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Notes

  • Fitingof B.M. (1966) Optimal Encoding under an Unknown or Changing Statistics. Problems of Information Transmission, Vol. 2 (2), P. 3–11.

    MathSciNet  MATH  Google Scholar 

  • Kolmogorov A.N. (1965) Three Approaches to the Definition of the Concept 201Cthe Quantity of Information”. Problems of Information Transmission, Vol. 1(1), P. 3–11. (Rus).

    Google Scholar 

  • Davisson L. (1973) Universal Noiseless Coding. IEEE. Trans. Inf. Th., Vol. 19 (6), P. 783–795.

    Article  MathSciNet  MATH  Google Scholar 

  • Krichevskii R.E. (1968) A Relation Between the Plausibility of Information about a Source and Encoding Redundancy. Problems of Information Transmission. Vol. 4, N 3, P. 48–57. (Rus).

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  • Ryabko B.Ja. (1980,a) Universal Encoding of Compacts. Dokl. Acad. Sci. USSR. Vol. 252(6), P. 1325–1328. (Rus).

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  • Ryabko B.Ja. (1980,b) Information Compression by a Book Stack. Problems of Information Transmission. Vol. 16(4), P. 16–21. (Rus)

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  • Bentley J.L., Sleator D.D., Tarjan R.E., Wei V.K. (1986) A Locally Adaptive Data Compression Scheme. Comm. of ACM, Vol. 29 (4), P. 320–330.

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© 1994 Springer Science+Business Media Dordrecht

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Krichevsky, R. (1994). Universal Codes. In: Universal Compression and Retrieval. Mathematics and Its Applications, vol 274. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-3628-2_5

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  • DOI: https://doi.org/10.1007/978-94-017-3628-2_5

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-4357-3

  • Online ISBN: 978-94-017-3628-2

  • eBook Packages: Springer Book Archive

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