Li, Yuhua, Pont, MJ, Parikh, CR and Jones, NB (2000) Comparing the performance of three neural classifiers for use in embedded applications. In: SOFT COMPUTING TECHNIQUES AND APPLICATIONS. UNSPECIFIED. 6 pp. [Conference contribution]
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In this paper, we provide a detailed empirical comparison of three neural-based classifiers used in embedded applications. The three techniques (multi-layer Perceptrons, radial basis function networks and adaptive fuzzy systems) are compared with one another and with a classical kNN classifier. In this study, we observe that the MLP provides similar levels of performance to the RBFN, AFS land kNN) classifiers while exerting a lower computational load on the processor.
|Item Type:||Conference contribution (Paper)|
|Keywords:||multi-layer perceptron network; radial basis function network; adaptive fuzzy system; k-nearest neighbour; embedded system|
|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 16:13|
|Last Modified:||09 May 2016 10:51|
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