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

K. F. Leung, Hung Fat Frank Leung, H. K. Lam, S. H. Ling

Research output: Journal article publicationJournal articleAcademic researchpeer-review

16 Citations (Scopus)


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).
Original languageEnglish
Pages (from-to)464-471
Number of pages8
JournalIEEE Transactions on Industrial Electronics
Issue number2
Publication statusPublished - 1 Apr 2004


  • Electronic books (eBooks)
  • Genetic algorithm (GA)
  • Neural-fuzzy networks (NFNs)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Instrumentation

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