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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.
Gao et al. (Thu,) studied this question.