Li, Yuhua ![]() |
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) |
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Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Publisher: | Physica |
ISBN: | 9783790812572 |
Last Modified: | 07 Nov 2022 09:26 |
URI: | https://orca.cardiff.ac.uk/id/eprint/129135 |
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