Name
Abstract | ||
|---|---|---|
Controlling chaos is a concept which many researchers have recently focused their attention on. This paper proposes a back propagation neural network to control chaotic trajectories belonging to discrete-time systems in order to obtain their unsteady equilibrium and their limit cycles (multi-period orbits); improving problems that arise in other control methods, being equally effective when dealing with relatively small random dynamical noise. The obtained results have been very successful especially when dealing with chaotic dynamical systems |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/ICECS.1999.814391 | Electronics, Circuits and Systems, 1999. Proceedings of ICECS '99. The 6th IEEE International Conference |
Keywords | DocType | Volume |
backpropagation,chaos,discrete time systems,limit cycles,neural nets,nonlinear dynamical systems,backpropagation neural network,chaos control,chaotic nonlinear dynamical systems,chaotic trajectories,discrete-time systems,multi-period orbits,random dynamical noise,stable chaotic dynamical systems,unsteady equilibrium,limit cycle,control systems,neural networks,newton method | Conference | 3 |
ISBN | Citations | PageRank |
0-7803-5682-9 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hernandez, C. | 1 | 0 | 0.34 |
| Martinez, A. | 2 | 21 | 3.27 |
| Castellanos, J. | 3 | 0 | 0.34 |
| Mingo, L.F. | 4 | 0 | 0.34 |