A step towards the development of VHDL model for ANN based EMG signal classifier

The artificial neural network (ANN) is an information processing model which is developed from the inspiration of practical biological nervous system. ANNs are analogous to the human brain, which can perform a variety of complex tasks if configured properly through a learning process. The research w...

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Main Authors:	Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran
Format:	Conference or Workshop Item
Language:	English
Published:	2012
Subjects:	T Technology (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/25722/ http://irep.iium.edu.my/25722/ http://irep.iium.edu.my/25722/1/494_ICIEV12_A_Step.pdf

id	iium-25722
recordtype	eprints
spelling	iium-257222012-09-18T07:26:19Z http://irep.iium.edu.my/25722/ A step towards the development of VHDL model for ANN based EMG signal classifier Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran T Technology (General) TK Electrical engineering. Electronics Nuclear engineering The artificial neural network (ANN) is an information processing model which is developed from the inspiration of practical biological nervous system. ANNs are analogous to the human brain, which can perform a variety of complex tasks if configured properly through a learning process. The research work involves with the utilization of ANN as a classifier for hand motion detection by using Electromyography (EMG) signals. A feed-forward ANN with back-propagation learning algorithm is used for the classification of EMG signals. This paper illustrates the modeling of the neural network based classifier using Hardware Description Language (HDL) for hardware realization. VHDL (Very High Speed Integrated Circuit Hardware Description Language) has been used to model the algorithm and which can be implemented into the target device FPGA (Field Programmable Gate Array). The development process and simulation output are presented in details with the architectural design of the neural network. The designed model has been synthesized and fitted into Altera’s Stratix III, chipset EP3SE50F780I4L using the electronic design automation (EDA) software Quartus II version 9.1 Web Edition. 2012 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/25722/1/494_ICIEV12_A_Step.pdf Ahsan, Md. Rezwanul and Ibrahimy, Muhammad Ibn and Khalifa, Othman Omran (2012) A step towards the development of VHDL model for ANN based EMG signal classifier. In: IEEE/OSA/IAPR International Conference on Informatics, Electronics & Vision, 18-19 May, 2012, Dhaka, Bangladesh. http://iciev.org/ICIEV2012/
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General) TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran A step towards the development of VHDL model for ANN based EMG signal classifier
description	The artificial neural network (ANN) is an information processing model which is developed from the inspiration of practical biological nervous system. ANNs are analogous to the human brain, which can perform a variety of complex tasks if configured properly through a learning process. The research work involves with the utilization of ANN as a classifier for hand motion detection by using Electromyography (EMG) signals. A feed-forward ANN with back-propagation learning algorithm is used for the classification of EMG signals. This paper illustrates the modeling of the neural network based classifier using Hardware Description Language (HDL) for hardware realization. VHDL (Very High Speed Integrated Circuit Hardware Description Language) has been used to model the algorithm and which can be implemented into the target device FPGA (Field Programmable Gate Array). The development process and simulation output are presented in details with the architectural design of the neural network. The designed model has been synthesized and fitted into Altera’s Stratix III, chipset EP3SE50F780I4L using the electronic design automation (EDA) software Quartus II version 9.1 Web Edition.
format	Conference or Workshop Item
author	Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran
author_facet	Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran
author_sort	Ahsan, Md. Rezwanul
title	A step towards the development of VHDL model for ANN based EMG signal classifier
title_short	A step towards the development of VHDL model for ANN based EMG signal classifier
title_full	A step towards the development of VHDL model for ANN based EMG signal classifier
title_fullStr	A step towards the development of VHDL model for ANN based EMG signal classifier
title_full_unstemmed	A step towards the development of VHDL model for ANN based EMG signal classifier
title_sort	step towards the development of vhdl model for ann based emg signal classifier
publishDate	2012
url	http://irep.iium.edu.my/25722/ http://irep.iium.edu.my/25722/ http://irep.iium.edu.my/25722/1/494_ICIEV12_A_Step.pdf
first_indexed	2023-09-18T20:38:18Z
last_indexed	2023-09-18T20:38:18Z
_version_	1777409194432921600

A step towards the development of VHDL model for ANN based EMG signal classifier

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