Resource management for W-CDMA systems using artificial neural network / Siti Rahmah Tukiran
This report presents the application of Artificial Neural Network (ANN) for the prediction of resource management in W-CDMA systems. The objective is to determine whether MATLAB Artificial Neural Network (ANN) Toolbox could be used to predict the future resource demand of W-CDMA systems. Artificial...
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2008
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my.uitm.ir.680512022-10-31T08:20:07Z https://ir.uitm.edu.my/id/eprint/68051/ Resource management for W-CDMA systems using artificial neural network / Siti Rahmah Tukiran Tukiran, Siti Rahmah Neural networks (Computer science) Wireless communication systems. Mobile communication systems. Access control This report presents the application of Artificial Neural Network (ANN) for the prediction of resource management in W-CDMA systems. The objective is to determine whether MATLAB Artificial Neural Network (ANN) Toolbox could be used to predict the future resource demand of W-CDMA systems. Artificial Neural Network can be one of the promises for the future computing problems. They offer on ability to perform tasks efficiently from outside the scope of traditional processors. They offer an ability to perform task efficiently from outside the scope of traditional processor. They can recognize pattern within vast dataset and generalize those patterns into recommended courses of action to achieve desired target. The backpropagation algorithm of Artificial Neural Network has been chosen to train and test the data. This method is chosen since it is the fastest technique that can be used to produce a successful result. 2008 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/68051/1/68051.PDF Resource management for W-CDMA systems using artificial neural network / Siti Rahmah Tukiran. (2008) Degree thesis, thesis, Universiti Teknologi MARA (UiTM). |
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Neural networks (Computer science) Wireless communication systems. Mobile communication systems. Access control |
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Neural networks (Computer science) Wireless communication systems. Mobile communication systems. Access control Tukiran, Siti Rahmah Resource management for W-CDMA systems using artificial neural network / Siti Rahmah Tukiran |
| description |
This report presents the application of Artificial Neural Network (ANN) for the prediction of resource management in W-CDMA systems. The objective is to determine whether MATLAB Artificial Neural Network (ANN) Toolbox could be used to predict the future resource demand of W-CDMA systems. Artificial Neural Network can be one of the promises for the future computing problems. They offer on ability to perform tasks efficiently from outside the scope of traditional processors. They offer an ability to perform task efficiently from outside the scope of traditional processor. They can recognize pattern within vast dataset and generalize those patterns into recommended courses of action to achieve desired target. The backpropagation algorithm of Artificial Neural Network has been chosen to train and test the data. This method is chosen since it is the fastest technique that can be used to produce a successful result. |
| format |
Thesis |
| author |
Tukiran, Siti Rahmah |
| author_facet |
Tukiran, Siti Rahmah |
| author_sort |
Tukiran, Siti Rahmah |
| title |
Resource management for W-CDMA systems using artificial neural network / Siti Rahmah Tukiran |
| title_short |
Resource management for W-CDMA systems using artificial neural network / Siti Rahmah Tukiran |
| title_full |
Resource management for W-CDMA systems using artificial neural network / Siti Rahmah Tukiran |
| title_fullStr |
Resource management for W-CDMA systems using artificial neural network / Siti Rahmah Tukiran |
| title_full_unstemmed |
Resource management for W-CDMA systems using artificial neural network / Siti Rahmah Tukiran |
| title_sort |
resource management for w-cdma systems using artificial neural network / siti rahmah tukiran |
| publishDate |
2008 |
| url |
https://ir.uitm.edu.my/id/eprint/68051/1/68051.PDF https://ir.uitm.edu.my/id/eprint/68051/ |
| _version_ |
1748705995027120128 |
| score |
13.211869 |