• DocumentCode
    324580
  • Title

    State-space central theory based analysis of feedforward neural networks

  • Author

    Craddock, R.J. ; Warwick, K.

  • Author_Institution
    Dept. of Cybern., Reading Univ., UK
  • Volume
    2
  • fYear
    1998
  • fDate
    4-9 May 1998
  • Firstpage
    1383
  • Abstract
    This paper presents a novel way of analysing feedforward neural networks. The analysis is performed using concepts and theory from state space control theory. Although feedforward neural networks are not strictly dynamic, the theory can be suitably adapted for application to such networks. By considering the concepts in a broad sense, a great deal of information about feedforward neural networks and a better understanding of how feedforward neural networks operate can be obtained
  • Keywords
    controllability; feedforward neural nets; observability; performance evaluation; state-space methods; controllability; feedforward neural networks; observability; state space; Control theory; Controllability; Equations; Feedforward neural networks; Mathematics; Neural networks; Neurofeedback; Output feedback; Recurrent neural networks; State-space methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-4859-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.1998.685977
  • Filename
    685977