Name
Abstract | ||
|---|---|---|
In this paper, we present a new approach for chaos reproduction using variable structure recurrent neural networks (VSRNN). A neural network identifier is designed, with a variable structure that will change according to its output performance as compared to the given orbits of an unknown chaotic systems. A tradeoff between identification errors and computational complexity is discussed. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/TNN.2004.836236 | IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council |
Keywords | Field | DocType |
identification error,identification,neurocontrollers,chaos,chaos generation,recurrent neural networks,chaos reproduction,computational complexity,neural network identifier,nonlinear control systems,variable structure recurrent neural network,recurrent neural nets,chaotic system,variable structure system,variable structure systems | Recurrent neural nets,Identifier,Pattern recognition,Computer science,Recurrent neural network,Time delay neural network,Chaotic systems,Artificial intelligence,Variable structure system,Artificial neural network,Machine learning,Computational complexity theory | Journal |
Volume | Issue | ISSN |
15 | 6 | 1045-9227 |
Citations | PageRank | References |
4 | 0.47 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ramon A. Felix | 1 | 16 | 2.69 |
| Sanchez, Edgar N. | 2 | 78 | 9.09 |
| Guanrong Chen | 3 | 12378 | 1130.81 |