Spike-based Control Algorithms

Spike-Based Control Algorithms is a class of neuromorphic control strategies that utilize discrete, event-driven spike signals to encode and process information, distinguishing itself through its emulation of biological neural dynamics for real-time, low-power closed-loop system regulation.

11

Publications

507

Citations

43

Authors

20

Institutions

Publications per year

2017–2026

3

Authors

43

  1. ÁJ
    Ángel Jiménez-Fernández

    Universidad de Sevilla, Spain

    2 publications · 69 citations

    2

    h-index

  2. AL
    Alejandro Linares-Barranco

    Universidad de Sevilla, Spain

    2 publications · 69 citations

    2

    h-index

  3. GJ
    G. Jiménez

    Universidad de Sevilla, Spain

    2 publications · 69 citations

    2

    h-index

  4. KH
    Kai Huang

    Sun Yat-sen University, China

    1 publications · 49 citations

    1

    h-index

  5. RE
    Robert E. Kass

    Carnegie Mellon University, United States

    1 publications · 141 citations

    1

    h-index

1–5 of 43

Venues

  1. Neural Networks

    2 publications · 190 citations

    2

    h-index

  2. 1

    h-index

  3. IEEE Access

    1 publications · 25 citations

    1

    h-index

  4. Sensors

    1 publications · 54 citations

    1

    h-index

  5. Neurocomputing

    1 publications · 16 citations

    1

    h-index

1–5