Using Polynomial Regression and Artificial Neural Networks for Reusable Analog IC Sizing

Nuno Lourenço 0003, Engin Afacan, Ricardo Martins 0003, Fábio Passos, António Canelas, Ricardo Póvoa, Nuno Horta, Günhan Dündar. Using Polynomial Regression and Artificial Neural Networks for Reusable Analog IC Sizing. In 16th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2019, Lausanne, Switzerland, July 15-18, 2019. pages 13-16, IEEE, 2019. [doi]

@inproceedings{0003A0PCPHD19,
  title = {Using Polynomial Regression and Artificial Neural Networks for Reusable Analog IC Sizing},
  author = {Nuno Lourenço 0003 and Engin Afacan and Ricardo Martins 0003 and Fábio Passos and António Canelas and Ricardo Póvoa and Nuno Horta and Günhan Dündar},
  year = {2019},
  doi = {10.1109/SMACD.2019.8795282},
  url = {https://doi.org/10.1109/SMACD.2019.8795282},
  researchr = {https://researchr.org/publication/0003A0PCPHD19},
  cites = {0},
  citedby = {0},
  pages = {13-16},
  booktitle = {16th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2019, Lausanne, Switzerland, July 15-18, 2019},
  publisher = {IEEE},
  isbn = {978-1-7281-1201-5},
}