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Viability of using ANN-BP on a handheld device

This paper discusses the feasibility of operating an artificial neural network - back propagation (ANN-BP) in a handheld device. Comparisons were done between operating an ANN-BP on a desktop versus a handheld device in duration of time and accuracy. It was found that by implementing an ANN-BP on a...

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Main Authors: Weng, L.Y., Omar, J.B., Siah, Y.K., Abidin, I.B.Z., Ahmed, S.K.
Format: Conference Paper
Language:English
Published: 2017
Online Access:http://dspace.uniten.edu.my/jspui/handle/123456789/6299
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spelling my.uniten.dspace-50232018-12-07T08:01:22Z Viability of using ANN-BP on a handheld device Weng, L.Y. Omar, J.B. Siah, Y.K. Abidin, I.B.Z. Ahmed, S.K. This paper discusses the feasibility of operating an artificial neural network - back propagation (ANN-BP) in a handheld device. Comparisons were done between operating an ANN-BP on a desktop versus a handheld device in duration of time and accuracy. It was found that by implementing an ANN-BP on a handheld device, the speed was slower as compared to running on a desktop. The accuracy of results did not differ much based on the device the ANN-BP was executed upon. As a conclusion, the viability of using a handheld device to run ANN-BP is not practical with current processor speeds as the processing time is approximately 300 times longer than that of a desktop. © 2010 IEEE. 2017-11-14T03:21:25Z 2017-11-14T03:21:25Z 2010 Conference Paper http://dspace.uniten.edu.my/jspui/handle/123456789/6299 10.1109/ICICCI.2010.82 en Proceedings - 2010 International Conference on Intelligent Computing and Cognitive Informatics, ICICCI 2010 2010, Article number 5566012, Pages 149-151
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description This paper discusses the feasibility of operating an artificial neural network - back propagation (ANN-BP) in a handheld device. Comparisons were done between operating an ANN-BP on a desktop versus a handheld device in duration of time and accuracy. It was found that by implementing an ANN-BP on a handheld device, the speed was slower as compared to running on a desktop. The accuracy of results did not differ much based on the device the ANN-BP was executed upon. As a conclusion, the viability of using a handheld device to run ANN-BP is not practical with current processor speeds as the processing time is approximately 300 times longer than that of a desktop. © 2010 IEEE.
format Conference Paper
author Weng, L.Y.
Omar, J.B.
Siah, Y.K.
Abidin, I.B.Z.
Ahmed, S.K.
spellingShingle Weng, L.Y.
Omar, J.B.
Siah, Y.K.
Abidin, I.B.Z.
Ahmed, S.K.
Viability of using ANN-BP on a handheld device
author_facet Weng, L.Y.
Omar, J.B.
Siah, Y.K.
Abidin, I.B.Z.
Ahmed, S.K.
author_sort Weng, L.Y.
title Viability of using ANN-BP on a handheld device
title_short Viability of using ANN-BP on a handheld device
title_full Viability of using ANN-BP on a handheld device
title_fullStr Viability of using ANN-BP on a handheld device
title_full_unstemmed Viability of using ANN-BP on a handheld device
title_sort viability of using ann-bp on a handheld device
publishDate 2017
url http://dspace.uniten.edu.my/jspui/handle/123456789/6299
_version_ 1644493592885985280
score 13.239859

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