• DocumentCode
    285192
  • Title

    High-order perceptrons for decoding error-correcting codes

  • Author

    Tseng, Yeun-Hsien ; WU, JA-LING

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan
  • Volume
    3
  • fYear
    1992
  • fDate
    7-11 Jun 1992
  • Firstpage
    24
  • Abstract
    The authors prove that the single-error correcting (2n-1, 2n-1-n) Hamming code and its extended single-error correcting/double-error detecting (2n, 2n-1-n) code can be decoded by low-complexity single-layer perceptrons which use high-order polynomials as their discriminant functions. It is illustrated that multiple-error correcting codes can be decoded by two-layer networks with high-order perceptrons in the first layer and linear perceptrons in the second layer
  • Keywords
    decoding; error correction codes; neural nets; polynomials; Hamming code; decoding; error-correcting codes; high-order perceptrons; high-order polynomials; linear perceptrons; neural nets; two-layer networks; Backpropagation; Computer science; Costs; Decoding; Error correction codes; Hopfield neural networks; Law; Multilayer perceptrons; Neural networks; Polynomials;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1992. IJCNN., International Joint Conference on
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    0-7803-0559-0
  • Type

    conf

  • DOI
    10.1109/IJCNN.1992.227042
  • Filename
    227042
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=285192