Weak Typicality

Weak Typicality is a probabilistic concept in information theory that characterizes a set of sequences whose empirical entropy is approximately equal to the true entropy of the source, within a specified tolerance, thereby distinguishing it from other typicality notions by focusing on the convergence of average log-probability rather than individual symbol frequencies.

17

Publications

1K

Citations

34

Authors

19

Institutions

Publications per year

2017–2026

2

Authors

34

  1. ER
    Eleanor Rosch

    University of California, Berkeley, United States

    2 publications · 560 citations

    2

    h-index

  2. GH
    Gerhard Heyer

    Leipzig University, Germany

    1 publications · 38 citations

    1

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  3. MR
    Maxim Raginsky

    University of Illinois Urbana-Champaign, United States

    1 publications · 23 citations

    1

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  4. CL
    Changquan Long

    Southwest University, China

    1 publications · 11 citations

    1

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  5. DS
    Daniela Spina

    University of Catania, Italy

    1 publications · 19 citations

    1

    h-index

1–5 of 34

Venues

  1. IEEE Transactions on Information Theory

    2 publications · 50 citations

    2

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  2. 2

    h-index

  3. Journal of Cleaner Production

    1 publications · 19 citations

    1

    h-index

  4. Theoretical Linguistics

    1 publications · 38 citations

    1

    h-index

  5. Scientific Reports

    1 publications · 11 citations

    1

    h-index

1–5