1. DSpaceCRIS@UNITEN
  2. College of Engineering
  3. COE Scholarly Publication
Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/5023
DC FieldValueLanguage
dc.contributor.authorWeng, L.Y.-
dc.contributor.authorOmar, J.B.-
dc.contributor.authorSiah, Y.K.-
dc.contributor.authorAbidin, I.B.Z.-
dc.contributor.authorAhmed, S.K.-
dc.date.accessioned2017-11-14T03:21:25Z-
dc.date.available2017-11-14T03:21:25Z-
dc.date.issued2010-
dc.identifier.urihttp://dspace.uniten.edu.my/jspui/handle/123456789/6299-
dc.description.abstractThis 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.-
dc.language.isoen-
dc.relation.ispartofProceedings - 2010 International Conference on Intelligent Computing and Cognitive Informatics, ICICCI 2010 2010, Article number 5566012, Pages 149-151-
dc.titleViability of using ANN-BP on a handheld device-
dc.typeConference Paper-
dc.identifier.doi10.1109/ICICCI.2010.82-
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:COE Scholarly Publication
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