ASIC Design of Nanoscale Artificial Neural Networks for Inference/Training by Floating-Point Arithmetic

Bibliographic Details
Authors: Niknia, Farzad|||0000-0002-4062-3638, Wang, Ziheng|||0000-0001-9668-7318, Liu, Shanshan|||0000-0001-6226-2880, Reviriego Vasallo, Pedro|||0000-0003-2540-5234, Louri, Ahmed|||0000-0003-4262-6688, Lombardi, Fabrizio|||0000-0003-3152-3245
Format: article
Publication Date:2024
Country:España
Institution:Universidad Politécnica de Madrid
Repository:Archivo Digital UPM
OAI Identifier:oai:oa.upm.es:80698
Online Access:https://oa.upm.es/80698/
Access Level:Open access
Keyword:Neurons
Training
Hardware
Backpropagation
Artificial neural networks
Vectors
Nanoscale devices
Artificial neural network (ANN)
multilayer perceptron (MLP)
floating-point
ASIC design
inference
training
Description
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