Analog-circuit implementation of multiplicative spike-timing-dependent plasticity with linear decay

DOI Web Site 被引用文献1件 参考文献32件
  • Moriya Satoshi
    Research Institute of Electrical Communication, Tohoku University
  • Kato Tatsuki
    Research Institute of Electrical Communication, Tohoku University
  • Oguchi Daisuke
    Research Institute of Electrical Communication, Tohoku University
  • Yamamoto Hideaki
    Research Institute of Electrical Communication, Tohoku University
  • Sato Shigeo
    Research Institute of Electrical Communication, Tohoku University
  • Yuminaka Yasushi
    Graduate School of Science and Technology, Gunma University
  • Horio Yoshihiko
    Research Institute of Electrical Communication, Tohoku University
  • Madrenas Jordi
    Department of Electronics Engineering, Polytechnic University of Catalonia

抄録

<p>Neuromorphic engineering is a promising computing paradigm in next-generation information and communication technology. In particular, spiking neural networks are expected to reduce power consumption drastically owing to their event-driven operation. The spike-timing-dependent plasticity (STDP) rule, which learns from local spike-timing differences between spiking neurons, is a biologically plausible learning rule for spiking neural networks (SNNs). In this study, we designed and simulated an analog circuit that reproduces the multiplicative STDP rule, which is more flexible and adaptive to external signals. We also derived analytical expressions for the behavior of the proposed circuit. These results provide important insights for designing energy efficient neuromorphic devices for applications including edge computing.</p>

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