A low-power synapse/neuron cell for artificial neural networks

A reconfigurable low-voltage low-power cell that can function either as a synapse or a neuron is proposed and analyzed in this article for the VLSI implementation of artificial neural networks (ANNs). The measured results are also presented. The design is based on the current-mode approach and uses the square-law characteristics of an MOS transistor working in saturation. The proposed fabricated synapse/neuron cell utilizes I–V converters, current mirror, and a ±1 V power supply to achieve superior performance. Modularity, ease of interconnectivity, expandability and reconfigurability are the main advantages of this cell.