Pseudo-random Pattern Generation

Pseudo-Random Pattern Generation is a method in built-in self-test systems that generates test patterns using deterministic algorithms to approximate randomness, enabling efficient and repeatable fault detection in digital circuits.

348

Publications

14.4K

Citations

816

Authors

312

Institutions

Publications per year

2017–2026

73

Variants

Prpg

Authors

816

  1. EM
    E.J. McCluskey

    Stanford University, United States

    11 publications · 474 citations

    10

    h-index

  2. JR
    Janusz Rajski

    Mentor Technologies, United States

    9 publications · 469 citations

    9

    h-index

  3. JT
    Jerzy Tyszer

    Poznań University of Technology, Poland

    9 publications · 451 citations

    9

    h-index

  4. GJ
    Gert Jervan

    Tallinn University of Technology, Estonia

    8 publications · 235 citations

    8

    h-index

  5. CL
    C. Landrault

    Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier, France

    7 publications · 163 citations

    7

    h-index

1–5 of 816

Venues

  1. 19

    h-index

  2. IEEE Transactions on Computers

    13 publications · 786 citations

    12

    h-index

  3. Journal of Electronic Testing

    JETTA · 8 publications · 238 citations

    8

    h-index

  4. IEEE Access

    8 publications · 206 citations

    8

    h-index

  5. Electronics Letters

    5 publications · 81 citations

    5

    h-index

1–5