Predicting Vt mean and variance from parallel Id measurement with model-fitting technique

@article{Tsai2016PredictingVM,
  title={Predicting Vt mean and variance from parallel Id measurement with model-fitting technique},
  author={Chih-Ying Tsai and Kao-Chi Lee and Chien-Hsueh Lin and Sung-Chu Yu and Wen-Rong Liau and Alex Chun-Liang Hou and Ying-Yen Chen and Chun-Yi Kuo and Jih-Nung Lee and Mango C.-T. Chao},
  journal={2016 IEEE 34th VLSI Test Symposium (VTS)},
  year={2016},
  pages={1-6}
}
To measure the variation of device Vt requires long test for conventional WAT test structures. This paper presents a framework that can efficiently and effectively obtain the mean and variance of Vt for a large number of DUTs. The proposed framework applies the model-based random forest as its core model-fitting technique to learn a model that can predict… CONTINUE READING