Spike-based Signal Processing

Spike-Based Signal Processing is a computational framework that processes information through discrete temporal events called spikes, distinguishing itself from continuous-value signal processing methods by encoding and transmitting data via the timing and frequency of these sparse, asynchronous pulses.

370

Publications

19.4K

Citations

1.1K

Authors

442

Institutions

Publications per year

2017–2026

130

Authors

1.1K

  1. TH
    Tiejun Huang

    Peking University, China

    12 publications · 496 citations

    13

    h-index

  2. AL
    Alejandro Linares-Barranco

    Universidad de Sevilla, Spain

    9 publications · 664 citations

    9

    h-index

  3. GJ
    G. Jiménez

    Universidad de Sevilla, Spain

    8 publications · 637 citations

    8

    h-index

  4. YT
    Yonghong Tian

    Peking University, China

    8 publications · 461 citations

    8

    h-index

  5. ZY
    Zhaofei Yu

    Peking University, China

    6 publications · 235 citations

    7

    h-index

1–5 of 1.1K

Venues

  1. Journal of Neuroscience Methods

    27 publications · 1.4K citations

    20

    h-index

  2. Neurocomputing

    16 publications · 525 citations

    14

    h-index

  3. Frontiers in Neuroscience

    11 publications · 557 citations

    12

    h-index

  4. Neural Computation

    11 publications · 580 citations

    11

    h-index

  5. 11

    h-index

1–5