On interpretation of Graffiti digits and characters for eBooks: Neural-fuzzy network and genetic algorithm approach

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Journal Article
IEEE Transactions on Industrial Electronics, 2004, 51 (2), pp. 464 - 471
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This paper presents the rule optimization, tuning of the membership functions, and optimization of the number of fuzzy rules, of a neural-fuzzy network (NFN) using a genetic algorithm (GA). The objectives are achieved by training a proposed NFN with rule switches. The proposed NFN and GA are employed to interpret graffiti number inputs and commands for electronic books (eBooks).
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