Lorrentz, P and Howells, WGJ and McDonald-Maier, KD (2010) Model learning from weights by adaptive enhanced probabilistic convergent network. In: UNSPECIFIED, ? - ?.
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Abstract
Current weightless classifiers require historical data to model a system and make prediction about a system successfully. Historical data either is not always available or does not take a recent system modification into consideration. For this reason an adaptive filter is designed, which when employed with a weightless classifier enables system model, difficult to characterise system model, and system output prediction, successfully. Results of experiments performed show that the fusion of an adaptive filter and a weightless classifier is more beneficial than the filter or the classifier utilised singly, and that no speed advantage is observed.
| Item Type: | Conference or Workshop Item (Paper) |
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| Additional Information: | Published proceedings: Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, ESANN 2010 |
| Divisions: | Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
| Depositing User: | Elements |
| Date Deposited: | 05 Jun 2020 08:16 |
| Last Modified: | 05 Jun 2020 08:16 |
| URI: | http://repository.essex.ac.uk/id/eprint/27791 |
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