Oxide-based analog synapse: Physical modeling, experimental characterization, and optimization

Analog switching in oxide synaptic device has been recently proposed as an important technology for realizing hardware neural network with online training ability. This paper develops a new physical model to quantify the analog weight modulation behaviors in the oxide-based analog synapse. The analog SET, RESET, and retention loss processes are simulated and verified by the experimental data measured from the fabricated HfO x based synapse. Based on the simulation results, key material parameters are captured, and optimization guidelines are provided.