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Design of neuron architecture on FPGA for electromechanical sensor signals / Khairudin Mohamad

Artificial neural networks (ANN) are known to be able to improve electrochemical sensor signal interpretation. The hardware realization of ANN requires investigation of many design issues relating to signal interfacing and design of a single neuron. This report focuses on the design of neuron archit...

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Main Author: Mohamad, Khairudin
Format: Thesis
Language:English
Published: 2012
Subjects:
TK Electrical engineering. Electronics. Nuclear engineering
Online Access:https://ir.uitm.edu.my/id/eprint/98642/1/98642.pdf
https://ir.uitm.edu.my/id/eprint/98642/
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spelling my.uitm.ir.986422024-07-28T16:07:14Z https://ir.uitm.edu.my/id/eprint/98642/ Design of neuron architecture on FPGA for electromechanical sensor signals / Khairudin Mohamad Mohamad, Khairudin TK Electrical engineering. Electronics. Nuclear engineering Artificial neural networks (ANN) are known to be able to improve electrochemical sensor signal interpretation. The hardware realization of ANN requires investigation of many design issues relating to signal interfacing and design of a single neuron. This report focuses on the design of neuron architecture on FPGA for electrochemical sensor signal. The objective of this project is to translate the data from electrochemical sensor signals and process the data with neuron structure and analyze how different digital module of the neuron could affect the data accuracy and performance of the design. It encompasses interfacing from analogue to digital, data structure and the design process of the simple neuron which includes adder, multiplier and multiplier accumulator (MAC). A major component of the algorithm is the design of the activation function. The chosen activation function is the hyperbolic tangent which is approximated by Taylor Series expansion. The neuron is evaluated on an Altera DE2-70 FPGA. The performances are evaluated in terms of functionality, usage of resources and timing analysis. For the data structure, it was demonstrated that increasing the fractional bits increases the precision. For the MAC was found that by using topology 2, propagation can be reducing up to 19.145ns 2012 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/98642/1/98642.pdf Design of neuron architecture on FPGA for electromechanical sensor signals / Khairudin Mohamad. (2012) Degree thesis, thesis, Universiti Teknologi MARA (UiTM).
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic TK Electrical engineering. Electronics. Nuclear engineering
spellingShingle TK Electrical engineering. Electronics. Nuclear engineering
Mohamad, Khairudin
Design of neuron architecture on FPGA for electromechanical sensor signals / Khairudin Mohamad
description Artificial neural networks (ANN) are known to be able to improve electrochemical sensor signal interpretation. The hardware realization of ANN requires investigation of many design issues relating to signal interfacing and design of a single neuron. This report focuses on the design of neuron architecture on FPGA for electrochemical sensor signal. The objective of this project is to translate the data from electrochemical sensor signals and process the data with neuron structure and analyze how different digital module of the neuron could affect the data accuracy and performance of the design. It encompasses interfacing from analogue to digital, data structure and the design process of the simple neuron which includes adder, multiplier and multiplier accumulator (MAC). A major component of the algorithm is the design of the activation function. The chosen activation function is the hyperbolic tangent which is approximated by Taylor Series expansion. The neuron is evaluated on an Altera DE2-70 FPGA. The performances are evaluated in terms of functionality, usage of resources and timing analysis. For the data structure, it was demonstrated that increasing the fractional bits increases the precision. For the MAC was found that by using topology 2, propagation can be reducing up to 19.145ns
format Thesis
author Mohamad, Khairudin
author_facet Mohamad, Khairudin
author_sort Mohamad, Khairudin
title Design of neuron architecture on FPGA for electromechanical sensor signals / Khairudin Mohamad
title_short Design of neuron architecture on FPGA for electromechanical sensor signals / Khairudin Mohamad
title_full Design of neuron architecture on FPGA for electromechanical sensor signals / Khairudin Mohamad
title_fullStr Design of neuron architecture on FPGA for electromechanical sensor signals / Khairudin Mohamad
title_full_unstemmed Design of neuron architecture on FPGA for electromechanical sensor signals / Khairudin Mohamad
title_sort design of neuron architecture on fpga for electromechanical sensor signals / khairudin mohamad
publishDate 2012
url https://ir.uitm.edu.my/id/eprint/98642/1/98642.pdf
https://ir.uitm.edu.my/id/eprint/98642/
_version_ 1806422115596894208
score 13.211869

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