Semi-markov Kernels

Semi-Markov Kernels is a mathematical construct in stochastic process theory that generalizes Markov transition kernels by incorporating explicit dwell-time distributions, thereby characterizing the probability of transitioning between states contingent on the duration spent in the current state.

54

Publications

3.3K

Citations

105

Authors

80

Institutions

Publications per year

2017–2026

25

Authors

105

  1. NL
    Nikolaos Limnios

    Université de Technologie de Compiègne, France

    8 publications · 242 citations

    8

    h-index

  2. HS
    Hao Shen

    Anhui University of Technology, China

    5 publications · 826 citations

    5

    h-index

  3. JH
    Ju H. Park

    Yeungnam University, South Korea

    5 publications · 375 citations

    5

    h-index

  4. LZ
    Lixian Zhang

    Harbin Institute of Technology, China

    5 publications · 599 citations

    5

    h-index

  5. QZ
    Quanxin Zhu

    Hunan Normal University, China

    3 publications · 181 citations

    3

    h-index

1–5 of 105

Venues

  1. IEEE Transactions on Automatic Control

    6 publications · 1.1K citations

    6

    h-index

  2. Journal of nonparametric statistics

    4 publications · 157 citations

    4

    h-index

  3. IEEE Transactions on Fuzzy Systems

    TFS · 4 publications · 334 citations

    4

    h-index

  4. 3

    h-index

  5. Reliability Engineering & System Safety

    2 publications · 248 citations

    2

    h-index

1–5