Title :
Chaos in the discrete time cellular neural networks
Author :
Yang, Chun-Mei ; Yang, Tao ; Zhang, Kan-Yu
Author_Institution :
Dept. of Mech. Eng., Shanghai Univ. of Technol., China
Abstract :
The quasi-period and chaos in discrete time cellular neural networks (DTCNN) are studied in this paper. In a 2-cell autonomous DTCNN, theories for periodic and quasi-periodic motions are presented. Chaos is found in 2 and 3-cell autonomous and nonautonomous DTCNNs. The structures of the strange attractors are shown. The bifurcation diagrams are used to show the transition procedures of the DTCNNs from the periodic motion to chaos. A strange attractor with 2 separated branches is also found in a 3-cell DTCNN
Keywords :
bifurcation; cellular neural nets; chaos; discrete time systems; nonlinear dynamical systems; 2-cell autonomous DTCNN; 3-cell autonomous DTCNN; 3-cell nonautonomous DTCNN; DTCNN; bifurcation diagrams; chaos; discrete time cellular neural networks; nonlinear discrete time dynamical systems; periodic motion; periodic motions; quasi-period; quasi-periodic motions; separated branches; strange attractors; transition procedures; Cellular neural networks; Chaos; Equations; Erbium; Fractals; Hydrogen; Intelligent networks; Stochastic systems; Sufficient conditions; Voltage;
Conference_Titel :
Cellular Neural Networks and their Applications, 1994. CNNA-94., Proceedings of the Third IEEE International Workshop on
Conference_Location :
Rome
Print_ISBN :
0-7803-2070-0
DOI :
10.1109/CNNA.1994.381663
