• DocumentCode
    1102072
  • Title

    On-line neural network learning algorithm with exponential convergence rate

  • Author

    Zhao, Y.

  • Author_Institution
    Dept. of Electron. Eng., Hangzhou Univ., China
  • Volume
    32
  • Issue
    15
  • fYear
    1996
  • fDate
    7/18/1996 12:00:00 AM
  • Firstpage
    1381
  • Lastpage
    1382
  • Abstract
    A new on-line learning algorithm for feedforward neural networks is presented. This algorithm is realised by using a technique for minimum tracking of a time-dependent objective function. Theoretical analysis shows that it converges exponentially, and simulations show that it is very effective
  • Keywords
    convergence; feedforward neural nets; learning (artificial intelligence); exponential convergence rate; feedforward neural network; minimum tracking; on-line learning algorithm; simulation; time-dependent objective function;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:19960895
  • Filename
    511132
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1102072