Fuzzy Connectives as a Combination Tool in a Hybrid Multi-Neural System

Canuto, Anne and Fairhurst, Michael and Howells, Gareth (2003) Fuzzy Connectives as a Combination Tool in a Hybrid Multi-Neural System. International Journal of Neural Systems, 13 (2). 67-76. ISSN 01290657. (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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The set of fuzzy connectives can be seen as an important combination tool, such as in combining the antecedent sets of the rules, in multi-criteria decision making and in combining the outputs of neural classifiers in a multi-neural system. This papers investigates the performance of some fuzzy combination schemes applied to a multi hybrid neural system which is composed of neural and fuzzy neural networks. An empirical evaluation in a handwritten numeral recognition task is used to investigate the performance of the presented fuzzy methods with some existing combination methods. [ABSTRACT FROM AUTHOR]

Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics (see also: telecommunications), > TK7880 Applications of electronics (inc industrial & domestic) > TK7885 Computer engineering
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Yiqing Liang
Date Deposited: 15 Sep 2008 10:45
Last Modified: 23 May 2014 09:24
Resource URI: https://kar.kent.ac.uk/id/eprint/7592 (The current URI for this page, for reference purposes)
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