• DocumentCode
    2526618
  • Title

    Digital hardware implementation of Self-Organising Maps

  • Author

    Cutajar, M. ; Gatt, E. ; Micallef, J. ; Grech, I. ; Casha, O.

  • Author_Institution
    Dept. of Microelectron., Univ. of Malta, Msida, Malta
  • fYear
    2010
  • fDate
    26-28 April 2010
  • Firstpage
    1123
  • Lastpage
    1128
  • Abstract
    In this paper a digital hardware implementation of the Self-Organising Maps (SOMs) for the application of handwritten digit recognition is presented. Two methods were implemented: Euclidean and Manhattan method. The highest recognition rate for both methods was calculated through three testing techniques. The highest recognition rates obtained are 71.267% and 63.667% for the Euclidean and the Manhattan methods respectively. Both methods were implemented on the Xilinx Spartan-3 200K gates (XC3S200) to compare their speed performance and area consumed.
  • Keywords
    handwritten character recognition; self-organising feature maps; Euclidean method; Manhattan method; Xilinx Spartan-3 200K gates; digital hardware implementation; handwritten digit recognition; self-organising maps; Handwriting recognition; Hardware; Microelectronics; Neural networks; Neurofeedback; Neurons; Pattern recognition; Testing; Trade agreements; Writing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    MELECON 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference
  • Conference_Location
    Valletta
  • Print_ISBN
    978-1-4244-5793-9
  • Type

    conf

  • DOI
    10.1109/MELCON.2010.5476361
  • Filename
    5476361