Stationary Random Processes

Stationary Random Processes is a stochastic process in which the statistical properties such as the mean, variance, and autocorrelation remain constant over time, distinguishing it from non-stationary random processes by exhibiting time-invariant probabilistic behavior.

1.9K

Publications

181.8K

Citations

2.5K

Authors

983

Institutions

Publications per year

2017–2026

133

Authors

2.5K

  1. SM
    Simeon M. Berman

    New York University, United States

    10 publications · 1.4K citations

    10

    h-index

  2. HW
    Herman Wold

    Statistics Sweden, Sweden

    10 publications · 1.9K citations

    10

    h-index

  3. MR
    M. R. Leadbetter

    University of North Carolina at Chapel Hill, United States

    10 publications · 2.4K citations

    10

    h-index

  4. OE
    Ole E. Barndorff–Nielsen

    Aarhus University, Denmark

    9 publications · 431 citations

    9

    h-index

  5. AW
    Aleksander Weron

    Wrocław University of Science and Technology, Poland

    8 publications · 487 citations

    8

    h-index

1–5 of 2.5K

Venues

  1. IEEE Transactions on Information Theory

    85 publications · 5.1K citations

    36

    h-index

  2. Journal of Applied Probability

    JAP · 74 publications · 4.6K citations

    32

    h-index

  3. Stochastic Processes and their Applications

    60 publications · 2.1K citations

    27

    h-index

  4. Journal of the American Statistical Association

    38 publications · 5.6K citations

    27

    h-index

  5. Theory of Probability and Its Applications

    54 publications · 4K citations

    27

    h-index

1–5