Title :
Bifurcation phenomena from a simple hysteresis network
Author_Institution :
Dept. of Electr. Eng., Hosei Univ., Tokyo
fDate :
30 Apr-3 May 1995
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;
Conference_Titel :
Circuits and Systems, 1995. ISCAS '95., 1995 IEEE International Symposium on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2570-2
DOI :
10.1109/ISCAS.1995.519935