Finite-state Markov Chains

Finite-State Markov Chains is a stochastic process belonging to the class of Markov chains characterized by a discrete state space of finite cardinality, where the future state depends solely on the current state and not on the sequence of preceding states.

1.1K

Publications

75.6K

Citations

1.8K

Authors

770

Institutions

Publications per year

2017–2026

89

Variants

Finite-state Markov Chain

Authors

1.8K

  1. VK
    Vikram Krishnamurthy

    University of British Columbia, Canada

    16 publications · 892 citations

    14

    h-index

  2. RL
    Richard L. Tweedie

    Colorado State University, United States

    13 publications · 988 citations

    11

    h-index

  3. PW
    Peter W. Glynn

    Stanford University, United States

    11 publications · 645 citations

    11

    h-index

  4. GY
    George Yin

    Wayne State University, United States

    8 publications · 571 citations

    8

    h-index

  5. AD
    Arnaud Doucet

    University of Cambridge, United Kingdom

    8 publications · 1.1K citations

    8

    h-index

1–5 of 1.8K

Venues

  1. Journal of Applied Probability

    JAP · 61 publications · 3K citations

    28

    h-index

  2. Advances in Applied Probability

    AAP · 43 publications · 2.3K citations

    25

    h-index

  3. IEEE Transactions on Automatic Control

    32 publications · 2.1K citations

    24

    h-index

  4. IEEE Transactions on Information Theory

    36 publications · 5.8K citations

    24

    h-index

  5. The Annals of Mathematical Statistics

    27 publications · 5K citations

    19

    h-index

1–5