A 300mV Body-biased Silicon Neuron Circuit with High Robustness against Firing Frequency Variation

Abstract

This paper presents a body-biased silicon neuron circuit which is capable of operating at ultra-low-voltage supplies and achieves a stable firing frequency. The proposed neuron employs body-biased method to increase charging current into the membrane capacitors for compensating the extra leakage current in the subthreshold region. A second-order low-pass filter, using the property of energy storage in capacitors, is used to reset the membrane potential and implement firing frequency adaption mechanism. Body-biased transistors are as well employed as voltage-controlled resistors to control the current flowing through the membrane capacitance. The circuit is capable of obtaining precise firing frequencies by biasing the body voltages of critical PMOS transistors, which make the circuit usable for frequency coding Spiking Neural Network (SNN). The designed neuron is implemented in 55nm bulk CMOS technology with an area of 400 µm2 that consumes about 639fJ@1kHz. We present circuit post-layout simulation results and demonstrate the circuit’s ability to produce biologically plausible neural dynamics with compact designs, and compare the energy consumption and stability with published state-of-the-art neuron circuits. Finally, the proposed circuit is proved to maintain a good robustness over process variation and Monte Carlo analysis with relative error 2.43% in firing rate of approximate 145Hz.