• DocumentCode
    298398
  • Title

    An extended Hamming neural network for non binary pattern recognition

  • Author

    Garcia, Juan Carlos Sanchez ; Miyatake, Mariko Nakano ; Meana, Hector Perez ; De Rivera y Oyarzabal, Luis Nifio

  • Author_Institution
    Dept. of Electr. Eng., Univ. Autonoma Metropolitana, Mexico City, Mexico
  • Volume
    1
  • fYear
    1994
  • fDate
    3-5 Aug 1994
  • Firstpage
    607
  • Abstract
    An extended Hamming neural network structure is proposed for recognition of non binary input patterns. Proposed structure is based on splitting the input pattern into N binary input patterns, where N is the number of bits used for representing each pixel of the original input pattern. Subsequently each binary pattern is processed for a Hamming neural network. Finally the outputs of each binary neural network are used to identify the non binary input pattern. Simulation results show that proposed structures performs fairly well for input patterns with 40% of their pixels distorted
  • Keywords
    neural nets; pattern recognition; Hamming neural network; nonbinary pattern recognition; simulation; Algorithms; Artificial neural networks; Computer simulation; Data preprocessing; Hamming distance; Matrix decomposition; Neural networks; Noise figure; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1994., Proceedings of the 37th Midwest Symposium on
  • Conference_Location
    Lafayette, LA
  • Print_ISBN
    0-7803-2428-5
  • Type

    conf

  • DOI
    10.1109/MWSCAS.1994.519368
  • Filename
    519368