• DocumentCode
    3623409
  • Title

    Application of Prony signal analysis to recurrent neural networks

  • Author

    M. Farrokhi;C. Isik

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Syracuse Univ., NY, USA
  • Volume
    1
  • fYear
    1994
  • Firstpage
    413
  • Abstract
    Recurrent neural networks are highly nonlinear dynamic systems, and therefore it is not an easy task to analyze their dynamic behavior. The primary goal of this paper is to apply Prony signal analysis and a modified root locus technique to recurrent neural networks. The Prony method is compared with other linearization methods to analyze recurrent neural networks, and their performances are demonstrated using simulated examples.
  • Keywords
    "Signal analysis","Recurrent neural networks","Poles and zeros","Stability","Nonlinear dynamical systems","Equations","Nonlinear systems","Eigenvalues and eigenfunctions","Application software","Computer networks"
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
  • Print_ISBN
    0-7803-1901-X
  • Type

    conf

  • DOI
    10.1109/ICNN.1994.374198
  • Filename
    374198
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3623409