Canuto, Anne, Howells, Gareth, Fairhurst, Michael (1999) RePART: A modified fuzzy ARTMAP for pattern recognition. Computational Intelligence, 1625 . pp. 159-168. ISSN 0824-7935. (doi:10.1007/3-540-48774-3_19) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:17181)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
| Official URL: http://dx.doi.org/10.1007/3-540-48774-3_19 |
Abstract
Fuzzy ARTMAP has been proposed as a neural network architecture for supervised learning of recognition categories and multidimensional maps in response to arbitrary sequences of analog or binary input vectors [12]. In this paper, RePART, a proposal for a variant of Fuzzy ARTMAP is analysed. As in ARTMAP-IC, this variant uses distributed code processing and instance counting in order to calculate the set of neurons used to predict untrained data. However, it additionally uses a reward/punishment process and takes into account every neuron in the calculation process..
| Item Type: | Article |
|---|---|
| DOI/Identification number: | 10.1007/3-540-48774-3_19 |
| Subjects: |
Q Science > Q Science (General) T Technology > TK Electrical engineering. Electronics. Nuclear engineering |
| Institutional Unit: | Schools > School of Engineering, Mathematics and Physics > Engineering |
| Former Institutional Unit: |
Divisions > Division of Natural Sciences > School of Engineering and Digital Arts Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
|
| Depositing User: | M. Nasiriavanaki |
| Date Deposited: | 30 Jun 2009 06:33 UTC |
| Last Modified: | 20 May 2025 10:33 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/17181 (The current URI for this page, for reference purposes) |
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