Blind Identification of Wiener Models
2011 (English)In: Proceedings of the 18th IFAC World Congress, 2011, 5597-5602 p.Conference paper (Refereed)
This paper develops and illustrates methods for the identiﬁcation of Wiener model structures. These techniques are capable of accommodating the “blind” situation where the input excitation to the linear block is not observed. Furthermore, the algorithm developed here can accommodate a nonlinearity which need not be invertible, and may also be multivariable. Central to these developments is the employment of the Expectation Maximisation (EM) method for computing maximum likelihood estimates, and the use of a new approach to particle smoothing to eﬃciently compute stochastic expectations in the presence of nonlinearities.
Place, publisher, year, edition, pages
2011. 5597-5602 p.
Wiener model, Nonlinear systems, Maximum likelihood, System identiﬁcation, Parameter estimation
IdentifiersURN: urn:nbn:se:liu:diva-95593DOI: 10.3182/20110828-6-IT-1002.02610ISBN: 978-3-902661-93-7OAI: oai:DiVA.org:liu-95593DiVA: diva2:636431
18th IFAC World Congress, Milano, Italy, 28 August-2 September, 2011
FunderSwedish Foundation for Strategic Research Swedish Research Council