NAS based on hierarchical exploration reinforcement learning

This is the official source code repository of "A Novel Approach to Detecting Muscle Fatigue Based on sEMG by Using Neural Architecture Search Framework".

This framework is used to seek for high-performance neural networks. You can directly run the "new2QNN_main.py" file. We use multiple sEMG signals as the data_source and classify the fatigue states. You can change it to your own datasets.

If our work is helpful to you, please Star it and kindly Cite our paper as:

@article{WangNovel,
  author={Wang, Shurun and Tang, Hao and Wang, Bin and Mo, Jia},
  journal={IEEE Transactions on Neural Networks and Learning Systems}, 
  title={A Novel Approach to Detecting Muscle Fatigue Based on sEMG by Using Neural Architecture Search Framework}, 
  year={2023},
  volume={34},
  number={8},
  pages={4932-4943},
  doi={10.1109/TNNLS.2021.3124330}}