• DocumentCode
    1679375
  • Title

    Graffiti commands interpretation for eBooks using a self-structured neural network and genetic algorithm

  • Author

    Leung, K.F. ; Lam, H.K. ; Leung, F.H.F. ; Tam, P.K.S.

  • Author_Institution
    Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Kowloon, China
  • Volume
    3
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    2487
  • Lastpage
    2492
  • Abstract
    This paper presents the interpretation of graffiti commands for electronic books (eBooks). A neural network is employed to perform the graffiti interpretation. By introducing a switch to each link of the neural network, the structure of the neural network can be obtained and tuned automatically by a genetic algorithm (GA) with arithmetic crossover and non-uniform mutation. Simulation results on interpreting graffiti commands for eBooks using the proposed neural network are shown
  • Keywords
    character recognition equipment; computer graphic equipment; electronic publishing; genetic algorithms; graphical user interfaces; handwritten character recognition; neural net architecture; notebook computers; self-organising feature maps; symbol manipulation; touch sensitive screens; tuning; arithmetic crossover; electronic books; genetic algorithm; graffiti command interpretation; neural network link switch; neural network structure tuning; nonuniform mutation; self-structured neural network; simulation; Arithmetic; Computational modeling; Electronic publishing; Genetic algorithms; Genetic engineering; Genetic mutations; Neural networks; Personal digital assistants; Signal processing algorithms; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7278-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2002.1007533
  • Filename
    1007533