Sampled-data Modeling

Sampled-Data Modeling is a formal methodology within mixed-signal modeling that characterizes systems processing continuous-time signals through discrete-time representations by capturing signal dynamics at specific sampling instants, thereby enabling the analysis and design of systems where analog and digital components interact intermittently.

320

Publications

16.4K

Citations

682

Authors

329

Institutions

Publications per year

2017–2026

62

Authors

682

  1. JI
    Juan I. Yuz

    Federico Santa María Technical University, Chile

    10 publications · 432 citations

    10

    h-index

  2. GC
    Graham C. Goodwin

    University of Newcastle Australia, Australia

    10 publications · 419 citations

    10

    h-index

  3. TH
    Tomomichi Hagiwara

    Kyoto University, Japan

    8 publications · 299 citations

    8

    h-index

  4. CF
    Chung‐Chieh Fang

    University of Maryland, College Park, United States

    7 publications · 166 citations

    7

    h-index

  5. LM
    Leonid Mirkin

    Technion – Israel Institute of Technology, Israel

    6 publications · 399 citations

    6

    h-index

1–5 of 682

Venues

  1. IEEE Transactions on Automatic Control

    37 publications · 2.6K citations

    22

    h-index

  2. Automatica

    26 publications · 1.2K citations

    17

    h-index

  3. IEEE Transactions on Power Electronics

    14 publications · 1.7K citations

    13

    h-index

  4. International Journal of Control

    10 publications · 273 citations

    10

    h-index

  5. Journal of the Franklin Institute

    9 publications · 386 citations

    9

    h-index

1–5