• DocumentCode
    2265751
  • Title

    Robustness analysis of a class of neural networks

  • Author

    Liu, Derong ; Michel, Anthony N.

  • Author_Institution
    Dept. of Electr. Eng., Notre Dame Univ., IN, USA
  • fYear
    1993
  • fDate
    16-18 Aug 1993
  • Firstpage
    1077
  • Abstract
    We present a robustness analysis result for a class of neural networks. Specifically, we assume a set of bipolar vectors to be memories for a network, and we establish a sufficient condition under which the given set of vectors are also memories of the original network after perturbations on its parameters
  • Keywords
    content-addressable storage; network parameters; perturbation techniques; recurrent neural nets; associative memories; bipolar vectors; feedback neural networks; network parameters; perturbations; robustness analysis; Artificial intelligence; Associative memory; Equations; Intelligent networks; Network synthesis; Neural networks; Neurofeedback; Robust stability; Robustness; Sufficient conditions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1993., Proceedings of the 36th Midwest Symposium on
  • Conference_Location
    Detroit, MI
  • Print_ISBN
    0-7803-1760-2
  • Type

    conf

  • DOI
    10.1109/MWSCAS.1993.343271
  • Filename
    343271
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2265751