Efficient Neural Networks on the Edge with FPGAs by Optimizing an Adaptive Activation Function

Efficient Neural Networks on the Edge with FPGAs by Optimizing an Adaptive Activation Function

The implementation of neural networks (NNs) on edge devices enables local processing of wireless data, but faces challenges such as high computational complexity and memory requirements when deep neural networks (DNNs) are used. Shallow neural networks customized for specific problems are more effic...

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Bibliografiska uppgifter
Huvudupphovsmän: Yiyue Jiang, Andrius Vaicaitis, John Dooley, Miriam Leeser
Materialtyp: Artikel
Språk:English
Publicerad: MDPI AG 2024-03-01
Serie:Sensors
Ämnen:
adaptive activation function (AAF)
neural network
FPGA
deep learning
digital predistortion
Länkar:https://www.mdpi.com/1424-8220/24/6/1829

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https://www.mdpi.com/1424-8220/24/6/1829

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