End-to-End Rapid FPGA Prototyping for Embedded Proactive BMI Control

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Abstract

This paper presents an end-to-end rapid prototyping methodology that performs automated and efficient mapping of desired neural networks onto FPGA. The design automation agent is considered as Autobot. An early prototype with the hardware decoder generated on the FPGA has been built, and its functionality has been evaluated. The experimental results show that Autobot can offer rapid end-to-end prototyping for neural network hardware generation for proactive BMI control.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
PublisherIEEE
Publication date28. Sep 2020
Article number9258186
ISBN (Electronic)9781728173993
DOIs
Publication statusPublished - 28. Sep 2020
Event7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020 - Taoyuan, Taiwan, Province of China
Duration: 28. Sep 202030. Sep 2020

Conference

Conference7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
Country/TerritoryTaiwan, Province of China
CityTaoyuan
Period28/09/202030/09/2020
SeriesIEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)
Volume2020
ISSN2575-8284

Keywords

  • Brain-machine interface (BMI)
  • embedded system
  • feedforward neural network
  • FPGA

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