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
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