DocumentCode :
3645707
Title :
Prediction of chaos and bifurcation: an asymmetric basis function approach
Author :
H. Shibayama;T. Saito
Author_Institution :
EEE Dept., Hosei Univ., Tokyo, Japan
Volume :
4
fYear :
1997
Firstpage :
2251
Abstract :
This paper proposes an asymmetric basis function (ABF) network and considers its application for prediction of chaotic time series and bifurcation phenomena. Using chaotic time series from an autonomous circuit, we have performed numerical simulation for the prediction problems and have confirmed that the ABF network has much better performance than conventional RBF networks.
Keywords :
"Chaos","Bifurcation","Radial basis function networks","Sampling methods","Diodes","Switches","Gaussian processes","Circuits","Convergence","Equations"
Publisher :
ieee
Conference_Titel :
Neural Networks,1997., International Conference on
Print_ISBN :
0-7803-4122-8
Type :
conf
DOI :
10.1109/ICNN.1997.614391
Filename :
614391
Link To Document :
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