FPGA implementation of back propagation neural network

This project presented a backpropagation neural network on FPGA which can conduct inference and training processes for linear and non-linear problems. The network structure chosen contains 3 input nodes, one hidden layer with three neuron units and 1 output node. In addition, this project compare...

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Bibliographic Details
Main Author:	Li, Jianing
Other Authors:	Zheng Yuanjin
Format:	Thesis-Master by Coursework
Language:	English
Published:	Nanyang Technological University 2022
Subjects:	Engineering::Electrical and electronic engineering::Applications of electronics
Online Access:	https://hdl.handle.net/10356/159255
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Institution:	Nanyang Technological University
Language:	English

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spelling	sg-ntu-dr.10356-1592552022-06-10T04:21:17Z FPGA implementation of back propagation neural network Li, Jianing Zheng Yuanjin School of Electrical and Electronic Engineering Zheng Yuanjin YJZHENG@ntu.edu.sg Engineering::Electrical and electronic engineering::Applications of electronics This project presented a backpropagation neural network on FPGA which can conduct inference and training processes for linear and non-linear problems. The network structure chosen contains 3 input nodes, one hidden layer with three neuron units and 1 output node. In addition, this project compares the training time between MATLAB and FPGA. The FPGA can achieve a much shorter training time owing to architecture advantage and computation data type simplification. In the end, the result of the neural network is displayed on the LEDs on the FPGA board. Keywords: Master of Science (Electronics) 2022-06-10T04:21:17Z 2022-06-10T04:21:17Z 2022 Thesis-Master by Coursework Li, J. (2022). FPGA implementation of back propagation neural network. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/159255 https://hdl.handle.net/10356/159255 en application/pdf Nanyang Technological University
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Electrical and electronic engineering::Applications of electronics
spellingShingle	Engineering::Electrical and electronic engineering::Applications of electronics Li, Jianing FPGA implementation of back propagation neural network
description	This project presented a backpropagation neural network on FPGA which can conduct inference and training processes for linear and non-linear problems. The network structure chosen contains 3 input nodes, one hidden layer with three neuron units and 1 output node. In addition, this project compares the training time between MATLAB and FPGA. The FPGA can achieve a much shorter training time owing to architecture advantage and computation data type simplification. In the end, the result of the neural network is displayed on the LEDs on the FPGA board. Keywords:
author2	Zheng Yuanjin
author_facet	Zheng Yuanjin Li, Jianing
format	Thesis-Master by Coursework
author	Li, Jianing
author_sort	Li, Jianing
title	FPGA implementation of back propagation neural network
title_short	FPGA implementation of back propagation neural network
title_full	FPGA implementation of back propagation neural network
title_fullStr	FPGA implementation of back propagation neural network
title_full_unstemmed	FPGA implementation of back propagation neural network
title_sort	fpga implementation of back propagation neural network
publisher	Nanyang Technological University
publishDate	2022
url	https://hdl.handle.net/10356/159255
_version_	1735491290578026496

FPGA implementation of back propagation neural network

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