An Analog-Digital Neural Processor for Integrated Sensor Conditioning

In this work a CMOS neural processor is presented. Based on a mixed analog-digital architecture, the system processes data in analog current mode, using digital registers to store weights safely. The proposed processor consists of two main blocks: A mixed-signal four-quadrant multiplier and a class AB current conveyor that implements the non-linear output function. Achieved from the circuit-level simulation, the neuron system-level model is used to study the application of this architecture to tackle linearization of a magnetoresistive sensor. Simulation results show the efficiency of the new implementation.