FPGA implementation of deep-learning recurrent neural networks with sub-millisecond real-time latency for BCI-decoding of large-scale neural sensors (104 nodes)

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Christopher Heelan, Arto V. Nurmikko, Wilson Truccolo. FPGA implementation of deep-learning recurrent neural networks with sub-millisecond real-time latency for BCI-decoding of large-scale neural sensors (104 nodes). In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018, Honolulu, HI, USA, July 18-21, 2018. pages 1070-1073, IEEE, 2018. [doi]

@inproceedings{HeelanNT18,
  title = {FPGA implementation of deep-learning recurrent neural networks with sub-millisecond real-time latency for BCI-decoding of large-scale neural sensors (104 nodes)},
  author = {Christopher Heelan and Arto V. Nurmikko and Wilson Truccolo},
  year = {2018},
  doi = {10.1109/EMBC.2018.8512415},
  url = {https://doi.org/10.1109/EMBC.2018.8512415},
  researchr = {https://researchr.org/publication/HeelanNT18},
  cites = {0},
  citedby = {0},
  pages = {1070-1073},
  booktitle = {40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018, Honolulu, HI, USA, July 18-21, 2018},
  publisher = {IEEE},
  isbn = {978-1-5386-3646-6},
}

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FPGA implementation of deep-learning recurrent neural networks with sub-millisecond real-time latency for BCI-decoding of large-scale neural sensors (104 nodes)