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Comparing the performance of three neural classifiers for use in embedded applications

Li, Y, Pont, MJ, Parikh, CR and Jones, NB 2000, Comparing the performance of three neural classifiers for use in embedded applications , in: Recent Advances in Soft Computing Techniques and Applications, 1-2 July 1999, Leicester, UK.

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Abstract

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 or Workshop Item (Paper)
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Advances in Soft Computing
Publisher: Physica-Verlag: Heidelberg
Refereed: Yes
Series Name: Advances in Soft Computing
Funders: Non funded research
Depositing User: Yuhua Li
Date Deposited: 27 Jul 2015 11:00
Last Modified: 05 Apr 2016 18:18
URI: http://usir.salford.ac.uk/id/eprint/33142

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