RePART: A modified fuzzy ARTMAP for pattern recognition

Canuto, Anne and Howells, Gareth and Fairhurst, Michael (1999) RePART: A modified fuzzy ARTMAP for pattern recognition. Computational Intelligence, 1625 . pp. 159-168. ISSN 0824-7935. (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)

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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
Subjects: Q Science > Q Science (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts
Depositing User: M. Nasiriavanaki
Date Deposited: 30 Jun 2009 06:33
Last Modified: 30 Apr 2014 08:35
Resource URI: https://kar.kent.ac.uk/id/eprint/17181 (The current URI for this page, for reference purposes)
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