Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/159255
Title: FPGA implementation of back propagation neural network
Authors: Li, Jianing
Keywords: Engineering::Electrical and electronic engineering::Applications of electronics
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Li, J. (2022). FPGA implementation of back propagation neural network. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/159255
Abstract: 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:
URI: https://hdl.handle.net/10356/159255
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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