Floating-Point Approximation Enabling Cost-Effective and High-Precision Digital Implementation of FitzHugh-Nagumo Neural Networks

Y. Zuo, Ning Ning 0002, G. C. Qiao, J. H. Wu, Junhan Bao, X. Y. Zhang, J. Bai, F. H. Wu, Yang Liu, Qi Yu, S. G. Hu. Floating-Point Approximation Enabling Cost-Effective and High-Precision Digital Implementation of FitzHugh-Nagumo Neural Networks. IEEE Trans. Biomed. Circuits and Systems, 18(2):347-360, April 2024. [doi]

@article{ZuoNQWBZBWLYH24,
  title = {Floating-Point Approximation Enabling Cost-Effective and High-Precision Digital Implementation of FitzHugh-Nagumo Neural Networks},
  author = {Y. Zuo and Ning Ning 0002 and G. C. Qiao and J. H. Wu and Junhan Bao and X. Y. Zhang and J. Bai and F. H. Wu and Yang Liu and Qi Yu and S. G. Hu},
  year = {2024},
  month = {April},
  doi = {10.1109/TBCAS.2023.3327496},
  url = {https://doi.org/10.1109/TBCAS.2023.3327496},
  researchr = {https://researchr.org/publication/ZuoNQWBZBWLYH24},
  cites = {0},
  citedby = {0},
  journal = {IEEE Trans. Biomed. Circuits and Systems},
  volume = {18},
  number = {2},
  pages = {347-360},
}