Adaptive Boolean Logic Using Ferroelectrics Capacitors as Basic Units of Artificial Neurons and Its Implementation in FPGA

In this work we propose the implementation of boolean logic through artificial neurons with Ferroelectric Capacitor (FeCapacitor) as its basic unit on a reconfigurable hardware platform. Two neurons were implemented: the Perceptron and the Spiking Neuron model. Both neurons use the phenomenon of the hysteresis loop as an activation function and were embedded on a Field Gate Programmable Gate Array (FPGA) hardware platform. The implementations were carried out by Simulink models and hardware synthesizable blocks from DSP Builder software and the results are shown in the form of the models and the boolean functions implemented by them.