Li, Yuhua, Pont, MJ and Jones, NB (1999) A comparison of the performance of radial basis function and multi-layer perceptron networks in condition monitoring and fault diagnosis applications. In: CONDITION MONITORING `99, PROCEEDINGS, SWANSA, WALES. UNSPECIFIED. 6 pp. [Conference contribution]
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In this paper, we provide a detailed comparison of multi-layer Perceptron (MLP) and radial basis function (RBF) networks in embedded, microcontroller-based condition monitoring and fault diagnosis applications. On the basis of the studies presented here, it is concluded that the MLP provides similar levels of performance to the RBF network while exerting a low computational load on the processor.
|Item Type:||Conference contribution (Paper)|
|Keywords:||engine misfire detection; neural networks; multi-layer perception; radial basis function; condition monitoring; fault classification|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
|Research Institutes and Groups:||Computer Science Research Institute|
Computer Science Research Institute > Intelligent Systems Research Centre
|Deposited By:||Dr Yuhua Li|
|Deposited On:||09 Mar 2010 16:14|
|Last Modified:||09 May 2016 10:51|
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