Frequency Domain Identification with Generalized Orthonormal Basis Functions

@inproceedings{Vries1998FrequencyDI,
  title={Frequency Domain Identification with Generalized Orthonormal Basis Functions},
  author={Douwe K. de Vries and Paul M. J. Van den Hof},
  year={1998}
}
A method is considered for the identification of linear parametric models based on a least squares identification criterion that is formulated in the frequency domain. To this end, use is made of the empirical transfer function estimate (ETFE), identified from time-domain data. As a parametric model structure use is made of a finite expansion sequence in terms of recently introduced generalized basis functions, being generalizations of the classical pulse and Laguerre and Kautz types of bases… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 30 references

Frequency smoothing using Laguerre model,

W. R. Cluett, L. Wang
Proc. Inst. Elec. Eng. , • 1992
View 4 Excerpts
Highly Influenced

Identification of State-Space Models from Time and Frequency Domain Data

T. McKelvey
Linköping Studies in Sci. and Technol., Diss. no • 1995
View 1 Excerpt

Identification of model uncertainty for a compact disc pick-up mechanism,

E. T. van Donkelaar
Mech. Eng. Syst. and Contr. Group, Delft Univ. Technology, • 1995
View 1 Excerpt

An efficient frequency domain state-space identification algorithm: Robustness and stochastic analysis,

T. McKelvey, H. Akcay
Proc. 33rd IEEE Conf. Decision Contr ., Lake Buena Vista, • 1994
View 1 Excerpt

Identification of model uncertainty for control design,

D. K. De Vries
Ph.D. dissertation, Delft Univ. Technol., The Netherlands, • 1994
View 1 Excerpt

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