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Proceedings ArticleDOI

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

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TLDR
The experimental results show that Autobot can offer rapid end-to-end prototyping for neural network hardware generation for proactive BMI control and performs automated and efficient mapping of desired neural networks onto FPGA.
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.

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Proceedings ArticleDOI

Teaching Hardware Implementation of Neural Networks using High-Level Synthesis in Less Than Four Hours for Engineering Education of Intelligent Embedded Computing

TL;DR: The motivation and design of a mini-course to teach hardware implementation of neural networks using high-level synthesis (HLS) in less than four hours for engineering education of intelligent embedded computing is presented.
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