• DocumentCode
    2545226
  • Title

    Automatic sizing of neural networks for function approximation

  • Author

    Rigoni, Enrico ; Lovison, Alberto

  • Author_Institution
    Esteco srl, Trieste
  • fYear
    2007
  • fDate
    7-10 Oct. 2007
  • Firstpage
    2005
  • Lastpage
    2010
  • Abstract
    Neural networks (NN) are a very efficient and powerful function approximation tool. Inspired by the brain structure and functions, NN are usually trained with backpropagation learning algorithm. A detailed benchmark on standard functions is provided, supporting in particular the automatic choice of the number of neurons in the hidden layer.
  • Keywords
    backpropagation; function approximation; neural nets; automatic sizing; backpropagation learning algorithm; brain structure; hidden layer; neural networks; powerful function approximation tool; Backpropagation algorithms; Biological neural networks; Brain; Feedforward neural networks; Function approximation; Multi-layer neural network; Neural networks; Neurons; Training data; Transfer functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on
  • Conference_Location
    Montreal, Que.
  • Print_ISBN
    978-1-4244-0990-7
  • Electronic_ISBN
    978-1-4244-0991-4
  • Type

    conf

  • DOI
    10.1109/ICSMC.2007.4413933
  • Filename
    4413933
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2545226