• DocumentCode
    298569
  • Title

    Bifurcation phenomena from a simple hysteresis network

  • Author

    Jin´no, Kenya

  • Author_Institution
    Dept. of Electr. Eng., Hosei Univ., Tokyo
  • Volume
    2
  • fYear
    1995
  • fDate
    30 Apr-3 May 1995
  • Firstpage
    1001
  • Abstract
    In order to analyze artificial neural networks which can treat dynamical information, we consider the simple hysteresis network whose cross connections are uniform. Also, it has only two parameters: self feedback and DC term. For this simple hysteresis network, we analyze discontinuous period doubling like bifurcation set. Even if all self feedback parameters are same value, we discover chaotic response which is confirmed by Lyapunov exponents and continuous spectrum. In our previous works, we have analyzed much simpler cases. In this paper, we analyze bifurcation phenomena by numerical experiments and laboratory measurements
  • Keywords
    Lyapunov methods; bifurcation; neural nets; nonlinear dynamical systems; DC term; Lyapunov exponents; artificial neural networks; bifurcation phenomena; discontinuous period doubling; dynamical information; hysteresis network; self feedback; uniform cross connections; Artificial neural networks; Bifurcation; Chaos; Circuits; Equations; Hysteresis; Information analysis; Neurofeedback; Oscillators; State feedback;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1995. ISCAS '95., 1995 IEEE International Symposium on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-2570-2
  • Type

    conf

  • DOI
    10.1109/ISCAS.1995.519935
  • Filename
    519935