Shannon Source Coding Theorem

The Shannon Source Coding Theorem is a fundamental theorem in information theory that establishes the theoretical limit for lossless data compression, specifying that the minimum average number of bits needed to represent each symbol of a source is bounded below by the source's entropy.

127

Publications

12.2K

Citations

176

Authors

95

Institutions

Publications per year

2017–2026

5

Variants

First Shannon TheoremShannon's Source Coding Theorem

Authors

176

  1. RM
    Robert M. Gray

    Stanford University, United States

    7 publications · 375 citations

    7

    h-index

  2. RZ
    Ram Zamir

    Tel Aviv University, Israel

    4 publications · 314 citations

    4

    h-index

  3. AW
    A.D. Wyner

    AT&T (United States), United States

    4 publications · 1.2K citations

    4

    h-index

  4. AS
    Anant Sahai

    University of California, Berkeley, United States

    4 publications · 70 citations

    4

    h-index

  5. MG
    Michael Gastpar

    University of California, Berkeley, United States

    3 publications · 132 citations

    3

    h-index

1–5 of 176

Venues

  1. IEEE Transactions on Information Theory

    50 publications · 5.8K citations

    31

    h-index

  2. 3

    h-index

  3. Proceedings of the IEEE

    3 publications · 108 citations

    3

    h-index

  4. The Annals of Probability

    2 publications · 53 citations

    2

    h-index

  5. Journal of the Franklin Institute

    2 publications · 43 citations

    2

    h-index

1–5