dc.contributor.authorChuang, Chun Tuan
dc.date.accessioned2017-05-17T02:23:29Z
dc.date.available2017-05-17T02:23:29Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10356/71472
dc.description.abstractAs big data becomes more easily available due to the increasing amount of smart electronics and communication devices, the need for big data analysis becomes more prevalent. One such method that can analyse big data is machine learning. Using Machine Learning, the computer will be able to analyse huge amounts of data in a short period of time. One of the ways to apply machine learning is through the use of Artificial Neural Networks(ANN). This report will discuss about two methods which uses ANN to implement machine learning to the system, specially, in the area of pattern recognition. Pattern recognition can help to classify the patterns seen into different classes, with each class having a specific meaning to the user that defines. This will help reduce the big data collected into smaller and more meaningful groupings.en_US
dc.format.extent77 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleDesign of activity tracker with on-board pattern recognition based on artificial neuron networken_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorSiek Literen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US


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