Blind maximum likelihood identification of Hammerstein systems

@article{Vanbeylen2008BlindML,
  title={Blind maximum likelihood identification of Hammerstein systems},
  author={Laurent Vanbeylen and Rik Pintelon and Johan Schoukens},
  journal={Automatica},
  year={2008},
  volume={44},
  pages={3139-3146}
}
This paper is about the identification of discrete-time Hammerstein systems from output measurements only (blind identification). Assuming that the unobserved input is white Gaussian noise, that the static nonlinearity is invertible, and that the output is observed without errors, a Gaussian maximum likelihood estimator is constructed. Its asymptotic properties are analyzed and the Cramér-Rao lower bound is calculated. In practice, the latter can be computed accurately without using the strong… CONTINUE READING