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An algorithm for selection of best orthonormal rational basis
KTH, Superseded Departments, Signals, Sensors and Systems.
KTH, Superseded Departments, Signals, Sensors and Systems.
KTH, Superseded Departments, Signals, Sensors and Systems.ORCID iD: 0000-0002-1927-1690
1997 (English)In: Decision and Control, 1997., Proceedings of the 36th IEEE Conference on, 1997, Vol. 2, 1277-1282 p.Conference paper (Refereed)
Abstract [en]

This paper deals with the problem of structure determination for generalized orthonormal basis models used in system identification. The model structure is parametrized by a pre-specified set of poles. Given this structure and experimental data a model can be estimated using linear regression techniques. Since the variance of the estimated model increases with the number of estimated parameters, the objective is to find structures that are as compact/parsimonious as possible. A natural approach would be to estimate the poles, but this leads to nonlinear optimization with possible local minima. In this paper, a best basis algorithm is derived for the generalized orthonormal rational bases. Combined with linear regression and thresholding this leads to compact transfer function representations

Place, publisher, year, edition, pages
1997. Vol. 2, 1277-1282 p.
Keyword [en]
discrete time systems;linear regression;model structure;orthonormal rational basis;parameter estimation;state space;system identification;thresholding;transfer function;discrete time systems;parameter estimation;state-space methods;statistical analysis;transfer functions;
National Category
Control Engineering
URN: urn:nbn:se:kth:diva-57957DOI: 10.1109/CDC.1997.657631OAI: diva2:472761
NR 20140805Available from: 2012-01-04 Created: 2012-01-04 Last updated: 2013-09-05Bibliographically approved

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