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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.
Kim et al. (Fri,) studied this question.