Robust nonlinear system identification using neural-network models

@article{Lu1998RobustNS,
  title={Robust nonlinear system identification using neural-network models},
  author={Songwu Lu and T. Basar},
  journal={IEEE transactions on neural networks},
  year={1998},
  volume={9 3},
  pages={407-29}
}
We study the problem of identification for nonlinear systems in the presence of unknown driving noise, using both feedforward multilayer neural network and radial basis function network models. Our objective is to resolve the difficulty associated with the persistency of excitation condition inherent to the standard schemes in the neural identification literature. This difficulty is circumvented here by a novel formulation and by using a new class of identification algorithms recently obtained… CONTINUE READING
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