The identification of nonlinear biological systems: Wiener and Hammerstein cascade models
Biological Cybernetics
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Phoneme analysis based on quantitative and qualitative entropy measurement
Computer Speech and Language
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Computers & Mathematics with Applications
A simple method to synchronize chaotic systems and its application to secure communications
Mathematical and Computer Modelling: An International Journal
Mathematical and Computer Modelling: An International Journal
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This paper describes two basic structures for identifying chaotic systems based on the Wiener and Hammerstein cascade models, in which three-layer feedforward artificial neural network is employed as the nonlinear static subsystem and a simple linear plant is used as the dynamic subsystem. Through training of the neural network and choosing an appropriate linear subsystem, various chaotic systems can be well identified by these two basic structures. Computer simulation results on Henon and Lozi systems are presented to demonstrate the effectiveness of these proposed structures. It is also shown that two chaotic systems whose outputs are different can actually exhibit similar chaotic attractors.