• DocumentCode
    1816426
  • Title

    A new neuron model for additional learning

  • Author

    Fukuda, Toshio ; Shiotani, Shigetoshi ; Arai, Fumihito

  • Author_Institution
    Dept. of Mech. Eng., Nagoya Univ., Japan
  • Volume
    1
  • fYear
    1992
  • fDate
    7-11 Jun 1992
  • Firstpage
    938
  • Abstract
    A novel neuron model called the new neural network (NNN) is proposed. It is shown that the NNN can learn and memorize additionally and recognize unlearned patterns by its generalization for two simulations on recognition. The NNN can recognize unlearned patterns more efficiently than backpropagation by the evaluation function in which the similarity is considered. The NNN has two excellent abilities: additional learning and superior generalization
  • Keywords
    learning (artificial intelligence); neural nets; pattern recognition; NNN; additional learning; backpropagation; neuron model; new neural network; unlearned patterns; Cities and towns; Humans; Image recognition; Mechanical engineering; Neural networks; Neurons; Pattern matching; Pattern recognition; Resonance; Subspace constraints;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1992. IJCNN., International Joint Conference on
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    0-7803-0559-0
  • Type

    conf

  • DOI
    10.1109/IJCNN.1992.287066
  • Filename
    287066