Titlebook: Errors-in-Variables Methods in System Identification; Torsten S?derstr?m Book 2018 Springer International Publishing AG, part of Springer

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Cerebral Cavernous Malformations (CCM)The chapter treats the method of covariance matching (CM). It is based on an optimization over higher dimension than GIVE, but results also in considerably more accurate parameter estimates. It is also described how the principle of factor analysis can be applied to dynamic systems, leading to essentially a covariance matching method.

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https://doi.org/10.1007/978-3-642-65814-3This chapter describes and analyzes maximum likelihood and prediction errormethods, tied to the EIV model used. Both time domain and frequency domain algorithms are treated. Various cases with different noise assumptions are included.

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https://doi.org/10.1007/978-1-4615-3824-0The chapter is devoted to some specific frequency domain methods. Both nonparametric and parametric estimators are presented. Further, frequency domain variants of the Frisch scheme and other GIVE estimators are given as well.

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James H. Fallon,Sandra E. LoughlinThe chapter treats total least squares (TLS), which in statistics corresponds to orthogonal regression. Some different extensions are discussed, including ways to show how uncertainties in different matrix elements may be related or correlated. The application of TLS to identification of dynamic systems is also treated.

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