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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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 |
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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 |
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1644493592885985280 |
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13.239859 |