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

Publication Type:
Journal Article
IEEE Transactions on Industrial Electronics, 2004, 51 (2), pp. 464 - 471
Issue Date:
Full metadata record
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).
Please use this identifier to cite or link to this item: