Bifurcations, chaos and control of chaos in spin-wave instabilities

1992 ◽  
Vol 104-107 ◽  
pp. 1041-1042 ◽  
Author(s):  
Antonio Azevedo ◽  
Sergio M. Rezende
1988 ◽  
Vol 49 (C8) ◽  
pp. C8-1599-C8-1600
Author(s):  
K. Nakamura ◽  
M. Mino ◽  
H. Yamazaki

Fractals ◽  
1997 ◽  
Vol 05 (03) ◽  
pp. 523-530 ◽  
Author(s):  
R. Bakker ◽  
R. J. de Korte ◽  
J. C. Schouten ◽  
C. M. Van Den Bleek ◽  
F. Takens

A neural-network-based model that has learnt the chaotic hydrodynamics of a fluidized bed reactor is presented. The network is trained on measured electrical capacitance tomography data. A training algorithm is used that does not only minimize the short-term prediction error but also the information needed to synchronize the model with the real system. This forces the model to focus more on learning the longer term dynamics of the system, expressed in the average multi-step-ahead prediction error and dynamic invariants such as correlation entropy and dimension. The availability of the model is an important step towards control of chaos in gas-solid fluidized beds.


1992 ◽  
pp. 129-155 ◽  
Author(s):  
H. Benner ◽  
F. Rödelsperger ◽  
G. Wiese

1964 ◽  
Vol 13 (21) ◽  
pp. 614-616 ◽  
Author(s):  
H. Matthews ◽  
F. R. Morgenthaler
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document