Overflow Handling Integrate-and-Fire Silicon-on-Insulator Neuron Circuit Incorporating a Schmitt Trigger Implemented by Back-Gate Effect

Taehyung Kim; Young Suh Song; Byung-Gook Park

doi:10.1166/jnn.2019.17004

Overflow Handling Integrate-and-Fire Silicon-on-Insulator Neuron Circuit Incorporating a Schmitt Trigger Implemented by Back-Gate Effect

J Nanosci Nanotechnol. 2019 Oct 1;19(10):6183-6186. doi: 10.1166/jnn.2019.17004.

Authors

Taehyung Kim¹, Young Suh Song¹, Byung-Gook Park¹

Affiliation

¹ Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Republic of Korea.

PMID: 31026933
DOI: 10.1166/jnn.2019.17004

Abstract

In this research, we propose an Integrate-and-fire (I&F) Silicon-on-insulator (SOI) neuron circuit incorporating a Schmitt trigger as an action potential generating component. The Schmitt trigger is composed of four MOSFETs, and it presents hysteresis by controlling the threshold of one of the four MOSFET using back-gate effect. The presented circuit effectively handles input overflow by modulating output pulse duration, thus maintaining Rectified-linear-unit (ReLU) equivalence of I&F spiking neuron. The effect of overflow handling by output pulse modulation was further investigated by comparing the performance of single-layer spiking neural network (SNN) implemented using proposed circuit and conventional circuit. The ex-situ (offline) triained SNN implemented using the proposed circuit showed 1.8%p accuracy improvement in classifying 1000 MNIST handwritten digits compared to one implemented using conventional I&F neuron circuit due to elimination of quantization error.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Action Potentials
Models, Neurological*
Neural Networks, Computer
Neurons
Silicon*

Substances

Silicon