A Perceptron Circuit with DAC-Based Multiplier for Sensor Analog Front-Ends

This paper presents a perceptron circuit which can be implemented into sensor analog front-end consistent with neural network-based machine learning. We introduce a DAC-based multiplier in the perceptron circuit, where the DAC is used as a programmable resistor. Compared with a traditional transconductor-based multiplier, the precision of our multiplier is formulated only by the digital codes, and it has a wide input range and a good temperature dependency. The simulation result demonstrates the DAC-based multiplier amplifies smoothly analog signals by the digital codes.