RRAM resistive switching behavior evaluation and prediction, based on fabrication conditions. Applied Machine learning\Deep learning models to predict SET voltage distribution in Honey-based RRAM devices.

The code in this repository is part of the following research paper:

Title: Supporting Green Neuromorphic Computing: Machine Learning Guided Microfabrication for Resistive Random Access Memory
Authors: Vicenciodelmoral, A. Y.; Tanim, M. M. H.; Zhao, F.; Zhao, X.
Conference: Presented at the 2022 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), Vancouver, WA, USA.
DOI: 10.1109/BDCAT56447.2022.00026