Shannon Source Coding

Shannon Source Coding is a foundational theory in information theory that establishes the limits of data compression by determining the minimum number of bits required to represent a source's output without loss of information, distinguishing it from channel coding and enabling the separation principle in communication system design.

78

Publications

5.7K

Citations

118

Authors

86

Institutions

Publications per year

2017–2026

3

Authors

118

  1. HY
    H. Yamamoto

    The University of Tokyo, Japan

    4 publications · 233 citations

    4

    h-index

  2. RZ
    Ram Zamir

    Tel Aviv University, Israel

    3 publications · 116 citations

    3

    h-index

  3. DO
    Donald Ornstein

    Stanford University, United States

    2 publications · 70 citations

    2

    h-index

  4. DS
    D. Sakrison

    University of California, Berkeley, United States

    2 publications · 95 citations

    2

    h-index

  5. RA
    Rudolf Ahlswede

    Bielefeld University, Germany

    2 publications · 26 citations

    2

    h-index

1–5 of 118

Venues

  1. IEEE Transactions on Information Theory

    34 publications · 3.6K citations

    25

    h-index

  2. NASA Technical Reports Server (NASA)

    Repository · 2 publications · 74 citations

    2

    h-index

  3. Bell System Technical Journal

    BSTJ · 2 publications · 198 citations

    2

    h-index

  4. Proceedings of the IEEE

    2 publications · 98 citations

    2

    h-index

  5. Physical Review Letters

    PRL · 1 publications · 108 citations

    1

    h-index

1–5