Implementation and Characterization of an Integrate-and-Fire Neuron Circuit Using a Silicon Nanowire Feedback Field-Effect Transistor

  • Woo, Sola
  • Cho, Jinsun
  • Lim, Doohyeok
  • Park, Young-Soo
  • Cho, Kyoungah
  • ... Kim, Sangsig
Citations

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33
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36

초록

In this article, we propose an integrate-and-fire (IF) neuron circuit using a single-gated silicon nanowire feedback field-effect transistor that utilizes a positive feedback loop. The IF operations are investigated through mixed-mode technology computer-aided design simulations. The neuron circuit composed of four component transistors (plus one capacitor) exhibits a high firing frequency of similar to 20 kHz and low power and energy consumption of 7 mu W and 2.9 x 10(-15) J. The firing frequency and spiking voltage can be controlled through external biasing voltages. Our novel neuron circuit demonstrates a promising potential for use in spiking neural network hardware for very large-scale integration.

키워드

Feedback field-effect transistors (FBFETs)integrate-and-fire (IF) neuronpositive feedback loopspiking neural networks (SNNs)TCAD simulationSPIKINGNETWORK
제목
Implementation and Characterization of an Integrate-and-Fire Neuron Circuit Using a Silicon Nanowire Feedback Field-Effect Transistor
저자
Woo, SolaCho, JinsunLim, DoohyeokPark, Young-SooCho, KyoungahKim, Sangsig
DOI
10.1109/TED.2020.2995785
발행일
2020-07
유형
Article
저널명
IEEE Transactions on Electron Devices
67
7
페이지
2995 ~ 3000