• DocumentCode
    1245182
  • Title

    An adaptive training algorithm for back-propagation neural networks

  • Author

    Hsin, Hsi-Chin ; Li, Ching-Chung ; Sun, Mingui ; Sclabassi, Robert J.

  • Author_Institution
    Dept. of Electr. Eng., Pittsburgh Univ., PA, USA
  • Volume
    25
  • Issue
    3
  • fYear
    1995
  • fDate
    3/1/1995 12:00:00 AM
  • Firstpage
    512
  • Lastpage
    514
  • Abstract
    A dynamic learning rate for back-propagation training of artificial neural networks is proposed as a weighted average of direction cosines of the incremental weight vectors of the current and previous steps. Experiments on training an EEG-based sleep state pattern recognition scheme have demonstrated its improved performance
  • Keywords
    backpropagation; neural nets; EEG-based sleep state pattern recognition scheme; adaptive training algorithm; back-propagation neural networks; direction cosines weighted average; dynamic learning rate; Approximation algorithms; Artificial neural networks; Convergence; Least squares approximation; Neural networks; Neurons; Pattern recognition; Sleep; Sun; Surgery;
  • fLanguage
    English
  • Journal_Title
    Systems, Man and Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9472
  • Type

    jour

  • DOI
    10.1109/21.364864
  • Filename
    364864
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1245182