• DocumentCode
    3242784
  • Title

    Training algorithms for GSNf neural networks

  • Author

    de Carvalho, A. ; Bisset, D. ; Fairhurst, M.

  • Author_Institution
    Dept. of Comput. Sci. & Stat., Sao Paulo Univ., Brazil
  • fYear
    1996
  • fDate
    9-11 Dec 1996
  • Firstpage
    74
  • Lastpage
    79
  • Abstract
    This paper presents and analyses distinct learning strategies which have been used by GSNf architectures. Sharing the common feature of being one-shot learning, these strategies achieve different performances as key parameters are changed. These algorithms are evaluated against each other by taking into account the training time, saturation rates, learning conflict rates and recognition performance
  • Keywords
    feedforward neural nets; learning (artificial intelligence); neural net architecture; pattern recognition; GSN neural networks; goal seeking neurons; learning algorithm; learning conflict rates; multilayer neural nets; neural net architectures; pattern recognition; saturation rates; training time; Character recognition; Machine learning; Neural networks; Neurons; Postal services; Velocity measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cybernetic Vision, 1996. Proceedings., Second Workshop on
  • Conference_Location
    Sao Carlos
  • Print_ISBN
    0-8186-8058-X
  • Type

    conf

  • DOI
    10.1109/CYBVIS.1996.629443
  • Filename
    629443
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3242784