Compact Neuromorphic System with Four-Terminal Si-Based Synaptic Devices for Spiking Neural Networks

Jungjin Park, Min Woo Kwon, Hyungjin Kim, Sungmin Hwang, Jeong Jun Lee, Byung Gook Park

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

In this paper, we propose a compact neuromorphic system that can work with four-terminal Si-based synaptic devices for spiking neural networks. The system consists of Si-based floating-body synaptic transistors and integrate-and-fire neuron circuit. The synaptic device can change its weight using floating-body effect and charge injection into the floating gate. The neuron circuit integrates signals from the synaptic devices through current mirrors and generates an action-potential when the integrated signal value exceeds a threshold value. The generated action potential that is transmitted to postsynaptic neurons is simultaneously returned to the back gate of the synaptic device for the change of weight based on spike-timing-dependent-plasticity. As the four-terminal synaptic device can transmit preneuron signals and change its weight at the same time, we can constitute the compact neuromorphic system without additional switches or logic operation and emulate the operation of neuron with a minimum number of devices and power dissipation (3 pJ).

Original languageEnglish
Article number7893783
Pages (from-to)2438-2444
Number of pages7
JournalIEEE Transactions on Electron Devices
Volume64
Issue number5
DOIs
StatePublished - May 2017

Keywords

  • Action-potential
  • neuromorphic
  • neuron circuit
  • spike-timing-dependent-plasticity (STDP)
  • synaptic device

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