Low-Power Adaptive Integrate-and-Fire Neuron Circuit Using Positive Feedback FET Co-Integrated With CMOS

Abstract

The most important aspect of an artificial neuron circuit is energy consumption. An analog neuron circuit has a critical problem in that the energy consumption in the steady-state due to a short-circuit current in the first inverter is quite large. In this study, we first demonstrated an adaptive neuron circuit with a dual-gate positive feedback field-effect transistor (FBFET) and fabricated a neuron circuit by co-integrating the FBFET and a complementary metal-oxide semiconductor (CMOS) in a chip. The fabricated FBFET has an extremely low sub-threshold slope of less than 0.5 mV/dec and a low off current. The threshold voltage of the FBFET can be precisely controlled by the second gate bias. By adjusting the second gate bias, it is possible to implement spike-frequency adaptive characteristics in the neuron circuit. Moreover, the proposed neuron circuit with the FBFET can significantly reduce the power dissipation. In the neuron circuit, a short-circuit current is suppressed by adopting the FBFET in the first inverter. In a modified inverter with the FBFET, more than 50% total energy consumption was reduced by the FBFET. We implemented the modified inverter in which the FBFET is connected in parallel with an N-channel metal-oxide semiconductor. Moreover, we utilized the neural frequency adaptation characteristics in the neuron circuit by adjusting the threshold voltage of the FBFET. Finally, we analyzed the fabricated FBFET neuron circuit operation and power consumption compared to a conventional CMOS neuron circuit.

Keywords

• Integrate-and-fire neuron circuit
• low power
• positive feedback field-effect transistor
• short-circuit current
• spike-frequency adaptation