Neuromorphic technologies for novel hardware AI

Predicting the dynamic behavior of memristive devices using recurrent neural networks

Somayeh Rezaei, Benjamin Spetzler, Patrick Mäder

Charge-transport models provide quantitative and physically interpretable descriptions of memristive devices but are computationally prohibitive for highly iterative tasks in model-driven design workflows such as parameter space exploration, parameter extraction, and optimization…Read more