Capacitor-Less Low-Power Neuron Circuit with Multi-Gate Feedback Field Effect Transistor

Abstract

Recently, research on artificial neuron circuits imitating biological systems has been actively studied. The neuron circuit can implement an artificial neural network (ANN) capable of low-power parallel processing by configuring a biological neural network system in hardware. Conventional CMOS analog neuron circuits require many MOSFETs and membrane capacitors. Additionally, it has low energy efficiency in the first inverter stage connected to the capacitor. In this paper, we propose a low-power neuron circuit with a multi-gate feedback field effect transistor (FBFET) that can perform integration without a capacitor to solve the problem of an analog neuron circuit. The multi-gate FBFET has a low off-current due to its low operating voltage and excellent sub-threshold characteristics. We replace the n-channel MOSFET of the inverter with FBFET to suppress leakage current. FBFET devices and neuron circuits were analyzed using TACD and SPICE mixed-mode simulation. As a result, we found that the neuron circuit with multi-gate FBFET has a low subthreshold slope and can completely suppress energy consumption. We also verified the temporal and spatial integration of neuron circuits.