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