• DocumentCode
    3783732
  • Title

    Kolmogorov learning for feedforward networks

  • Author

    R. Neruda;A. Stedry;J. Drkosova

  • Author_Institution
    Inst. of Comput. Sci., Czechoslovak Acad. of Sci., Prague, Czech Republic
  • Volume
    1
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    77
  • Abstract
    We present a learning algorithm for feedforward neural networks that is based on Kolmogorov theorem concerning composition of a n-dimensional continuous function from a one-dimensional continuous functions. A thorough analysis of the algorithm time complexity is presented for its serial and parallel implementation.
  • Keywords
    "Neural networks","Clustering algorithms","Computer science","Feedforward neural networks","Algorithm design and analysis","Workstations","Computer networks","Quantum computing"
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2001. Proceedings. IJCNN ´01. International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7044-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2001.938995
  • Filename
    938995
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3783732